Google Data Analytics Professional Certificate Answers - Coursera

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Google Data Analytics Professional Certificate Answers - Coursera


Whether you’re just getting started or want to take the next step in the high-growth field of data analytics, professional certificates from Google can help you gain in-demand skills. You’ll learn about R programming, SQL, Python, Tableau and more.

Data analysts prepare, process, and analyze data to help inform business decisions. They create visualizations to share their findings with stakeholders and provide recommendations driven by data.

This certification is part of Google Career Certificates .

Complete a Google Career Certificate to get exclusive access to CareerCircle, which offers free 1-on-1 coaching, interview and career support, and a job board to connect directly with employers, including over 150 companies in the Google Career Certificates Employer Consortium.


Language: English

 

Certification URLs:

grow.google/certificates/data-analytics

coursera.org/google-certificates/data-analytics-certificate


Questions:


Course 1 – Foundations: Data, Data, Everywhere

 

Week 1 – Introducing data analytics

 

Fill in the blank: A collection of elements that interact with one another to produce, manage, store, organize, analyze, and share data is known as a data ______ .

  • environment
  • ecosystem
  • model
  • cloud

 

Fill in the blank: In data science, ________ is when a data analyst uses their unique past experiences to understand the story the data is telling.

  • rational thought
  • gut instinct
  • personal opinion
  • awareness

 

Fill in the blank: When posting in a discussion forum, you should make sure that any articles discussed are _______ to data analytics.

  • unique
  • well known
  • relevant
  • popular

 

  1. Data analysis is the various elements that interact with one another in order to provide, manage, store, organize, analyze, and share data.
  • True
  • False

 

  1. In data analytics, a model is a group of elements that interact with one another.
  • True
  • False

 

  1. Fill in the blank: The primary goal of a data _____ is to create new questions using data.
  • designer
  • analyst
  • engineer
  • scientist

 

  1. Fill in the blank: The term _____ is defined as an intuitive understanding of something with little or no explanation.
  • personal opinion
  • rational thought
  • gut instinct
  • awareness

 

  1. A company defines a problem it wants to solve. Then, a data analyst gathers relevant data, analyzes it, and uses it to draw conclusions. The analyst shares their analysis with subject-matter experts, who validate the findings. Finally, a plan is put into action. What does this scenario describe?
  • Data science
  • Data-driven decision-making
  • Customer service
  • Identification of trends

 

  1. What do subject-matter experts do to support data-driven decision-making? Select all that apply.
  • Offer insights into the business problem
  • Review the results of data analysis and identify any inconsistencies
  • Collect, transform, and organize data
  • Validate the choices made as a result of the data insights

 

  1. You have just finished analyzing data for a marketing project. Before moving forward, you share your results with members of the marketing team to see if they might have additional insights into the business problem. What practice does this support?
  • Data analytics
  • Data science
  • Data-driven decision-making
  • Data management

 

  1. You read an interesting article about data analytics in a magazine and want to share some ideas from the article in the discussion forum. In your post, you include the author and a link to the original article. This would be an inappropriate use of the forum.
  • True
  • False

 

  1. Which of the following options describes data analysis?
  • The various elements that interact with one another in order to provide, manage, store, organize, analyze, and share data
  • Creating new ways of modeling and understanding the unknown by using raw data
  • The collection, transformation, and organization of data in order to draw conclusions, make predictions, and drive informed decision-making
  • Using facts to guide business strategy

 

  1. In data analytics, what term describes a collection of elements that interact with one another to produce, manage, store, organize, analyze, and share data?
  • The cloud environment
  • A modeling system
  • A data ecosystem
  • A database

 

  1. Select the best description of gut instinct.
  • Choosing facts that complement your personal experiences
  • An intuitive understanding of something with little or no explanation
  • Manipulating data to match your intuition
  • Using your innate ability to analyze results

 

  1. A furniture manufacturer wants to find a more environmentally friendly way to make its products. A data analyst helps solve this problem by gathering relevant data, analyzing it, and using it to draw conclusions. The analyst then shares their analysis with subject-matter experts from the manufacturing team, who validate the findings. Finally, a plan is put into action. This scenario describes data-driven decision making.
  • True
  • False

 

  1. Fill in the blank: _______ are an important part of data-driven decision-making because they are people familiar with the business problem and can offer insight into the results of data analysis.
  • Customers
  • Competitors
  • Subject-matter experts
  • Stakeholders

 

  1. Consulting with experts in the marketing department about your marketing analysis is an example of what process?
  • Data analytics
  • Data-driven decision-making
  • Data management
  • Data science

 

  1. You have recently subscribed to an online data analytics magazine. You really enjoyed an article and want to share it in the discussion forum. Which of the following would be appropriate in a post? Select all that apply.
  • Checking your post for typos or grammatical errors.
  • Including an advertisement for how to subscribe to the data analytics magazine.
  • Giving credit to the original author.
  • Including your own thoughts about the article.

 

  1. Which of the following could be elements of a data ecosystem? Select all that apply
  • Sharing data
  • Producing data
  • Gaining insights
  • Managing data

 

  1. If you are using data-driven decision-making, what action steps would you take? Select all that apply.
  • Surveying customers about results, conclusions, and recommendations
  • Gathering and analyzing data
  • Sharing your results with subject matter experts
  • Drawing conclusions from your analysis

 

  1. What do subject-matter experts do to support data-driven decision-making? Select all that apply.
  • Collect, transform, and organize data
  • Offer insights into the business problem
  • Review the results of data analysis and identify any inconsistencies
  • Validate the choices made as a result of the data insights

 

  1. Fill in the blank: When following data-driven decision-making, a data analyst will consult with ______ .
  • subject matter experts
  • stakeholders
  • managers
  • customers

 

  1. What is the purpose of data analysis? Select all that apply.
  • To drive informed decision-making
  • To create models of data
  • To draw conclusions
  • To make predictions

 

  1. A data analyst is someone who does what?
  • Designs new products
  • Creates new questions using data
  • Solves engineering problems
  • Finds answers to existing questions by creating insights from data sources

 

  1. What tactics can a data analyst use to effectively blend gut instinct with facts? Select all that apply.
  • Use their knowledge of how their company works to better understand a business need.
  • Focus on intuition to choose which data to collect and how to analyze it.
  • Ask how to define success for a project, but rely most heavily on their own personal perspective.
  • Apply their unique past experiences to their current work, while keeping in mind the story the data is telling.

 

  1. To get the most out of data-driven decision-making, it’s important to include insights from people very familiar with the business problem. What are these people called?
  • Subject-matter experts
  • Customers
  • Stakeholders
  • Competitors

 

  1. A music streaming service is looking to increase user engagement on their platform. The CEO decides to leverage the company's user data and tasks the data analysts with uncovering unknown trends and characteristics of the companies user base. This strategy is known as what?
  • Data analytics decision-making
  • Data science decision-making
  • Data management decision-making
  • Data-driven decision-making

 

  1. You read an interesting article in a magazine and want to share it in the discussion forum. What should you do when posting? Select all that apply.
  • Check your post for typos or grammatical errors
  • Include your email address for people to send questions or comments
  • Make sure the article is relevant to data analytics
  • Take credit for creating the article

 

  1. A data scientist is someone who does what?
  • Creates new questions using data
  • Finds answers to existing questions by creating insights from data sources
  • Solves engineering problems
  • Solves engineering problems

 

  1. Data analysts act as detectives to uncover clues within the data. Like a detective, a data analyst may use their _______ to solve business problems.
  • personal opinion
  • rational thought
  • gut instinct
  • awareness

 

  1. In data-driven decision-making, a data analyst would share their results with subject matter experts and draw conclusions from their analysis. What else would a data analyst do in data-driven decision-making?
  • Identification of trends
  • Determining the stakeholders.
  • Survey customers about results, conclusions, and recommendations
  • Gather and analyze data

 

  1. Fill in the blank: _________ is the act of consulting with subject-matter experts about the results of your data analysis.
  • Data analytics
  • Data science
  • Data management
  • Data-driven decision-making

 

  1. Data ______ is the collection, transformation, and organization of data in order to draw conclusions, make predictions, and drive informed decision-making.
  • science
  • analysis
  • ecosystem
  • life cycle

 

  1. Fill in the blank: The primary goal of a data _____ is to find answers to existing questions by creating insights from data sources.
  • engineer
  • scientist
  • analyst
  • designer

 

  1. Sharing your results with subject matter experts and gathering and analyzing data are carried out in data driven-decision-making. What else is included in this process?
  • Determining the stakeholders
  • Identification of trends
  • Drawing conclusions from your analysis.
  • Surveying customers about results, conclusions, and recommendations

 

  1. Fill in the blank: The people very familiar with a business problem are called _____. They are an important part of data-driven decision-making.
  • subject-matter experts
  • customers
  • competitors
  • stakeholders

 

  1. Fill in the blank: When posting in a discussion forum, you should always check your post for _______ and grammatical errors
  • support
  • typos
  • importance
  • popularity

 

  1. Fill in the blank: Hardware, software, and the cloud all interact with each other to store and organize data in a _____.
  • cloud environment
  • modeling system
  • database
  • data ecosystem

 

  1. Gut instinct is an intuitive understanding of something with little or no explanation.
  • True
  • False

 

Week 2 – All about analytical thinking

 

Fill in the blank: Gathering additional information about data to understand the broader picture is an example of understanding _____.

  • problems
  • data
  • knowledge
  • context

 

Correlation is the aspect of analytical thinking that involves figuring out the specific details that help you execute a plan.

  • True
  • False

 

What method involves asking multiple questions in order to get to the root cause of a problem?

  • The five whys
  • Strategizing
  • Curiosity
  • Inquiry

 

  1. A junior data analyst is seeking out new experiences in order to gain knowledge. They watch videos and read articles about data analytics. They ask experts questions. Which analytical skill are they using?
  • Data strategy
  • Having a technical mindset
  • Curiosity
  • Understanding context

 

 

  1. Identifying the motivation behind data collection and gathering additional information are examples of which analytical skill?
  • Data design
  • A technical mindset
  • Understanding context
  • Data strategy

 

  1. Having a technical mindset is an analytical skill involving what?
  • Managing people, processes, and tools
  • Understanding the condition in which something exists or happens
  • Breaking things down into smaller steps or pieces
  • Balancing roles and responsibilities

 

 

  1. Fill in the blank: Data strategy involves _____ the people, processes, and tools used in data analysis.
  • supervising
  • managing
  • choosing
  • visualizing

 

  1. Correlation is the aspect of analytical thinking that involves figuring out the specifics that help you execute a plan.
  • True
  • False

 

  1. What method involves asking numerous questions in order to get to the root cause of a problem?
  • Strategizing
  • The five whys
  • Curiosity
  • Inquiry

 

  1. Gap analysis is a method for examining and evaluating how a process works currently in order to get where you want to be in the future.
  • True
  • False

 

  1. Data-driven decision-making involves the five analytical skills: curiosity, understanding context, having a technical mindset, data design, and data strategy. Each plays a role in data-driven decision-making.
  • True
  • False

 

Shuffle Q/A

  1. Fill in the blank: The analytical skill of ______ involves seeking out new experiences in order to gain knowledge.
  • understanding context
  • having a technical mindset
  • data strategy
  • curiosity

 

  1. Breaking things down into smaller steps or pieces and working with them in an orderly and logical way describes which analytical skill?
  • Data strategy
  • Context
  • Curiosity
  • A technical mindset

 

  1. In data analysis, data strategy is the analytical skill that involves managing which of the following? Select all that apply.
  • People
  • Consent
  • Tools
  • Processes

 

  1. A grocery store owner notices that they sell more orange juice during the winter season, when people are more likely to get sick. After observing this for a couple of years, they decide to stock more orange juice during the winter. The store owner is using which quality of analytical thinking?
  • detail-oriented thinking
  • correlation
  • problem-orientation
  • visualization

 

  1. The five whys is a technique that involves asking, “Why?” five times in order to achieve what goal?
  • Identify the root cause of a problem
  • Visualize how a process should look in the future
  • Put a plan into action
  • Use facts to guide business strategy

 

  1. In data analysis, one often examines and evaluates how a process currently works in order to get it to where they want it to be in the future. This is known as what?
  • Building a data visualization
  • Gap analysis
  • Determining the stakeholders
  • Asking the five whys

 

  1. A company is seeing a decline in organizational efficiency. They decide to hire an outside organization to help increase overall performance. The data analyst, working for the newly contracted company, utilizes five analytical skills: curiosity, understanding context, having a technical mindset, data design, and data strategy to deliver the project goals. Once the project goals are met, the analyst informs the decision makers of their findings and the project is completed. What strategy did the data analyst use to complete this project?
  • Gut instinct
  • Gap analysis
  • Data-driven decision-making
  • The five whys

 

  1. Identifying the motivation behind the collection of a dataset is an example of the analytical skill of understanding context.
  • True
  • False

 

  1. A technical mindset involves the ability to break things down into smaller steps or pieces and work with them in an orderly and logical way.
  • True
  • False

 

  1. Data design is how you organize information; data strategy is the management of the people, processes, and tools used in data analysis.
  • True
  • False

 

  1. What method involves examining and evaluating how a process works currently in order to get where you want to be in the future?
  • The five whys
  • Strategy
  • Gap analysis
  • Data visualization

 

  1. Seeking out new challenges and experiences in order to learn is an example of which analytical skill?
  • Curiosity
  • Data strategy
  • Understanding context
  • Having a technical mindset

 

  1. Which of the following examples best describe the analytical skill of understanding context? Select all that apply.
  • Adding descriptive headers to columns of data in a spreadsheet
  • Working with facts in an orderly manner
  • Gathering additional information about data to understand the broader picture
  • Identifying the motivation behind the collection of a dataset

 

  1. Fill in the blank: In data analysis, data strategy involves managing the people, processes, and _____ .
  • projects
  • procedures
  • consent
  • tools

 

  1. Identifying a relationship between two or more pieces of data is known as what?
  • visualization
  • correlation
  • problem-orientation
  • detail-oriented thinking

 

  1. As a new data analyst, your boss asks you to perform a gap analysis on one of their current processes. What does this entail?
  • Building a data visualization
  • Asking the five whys
  • Examining and evaluating how a process works currently in order to get where you want to be in the future
  • Determining the stakeholders

 

  1. Fill in the blank: In data-driven decision making, data analysts use five analytical skills of curiosity, understanding context, having a technical mindset, data design, and _______ .
  • data strategy
  • forward-looking
  • intuition
  • efficiency

 

  1. The analytical skill of understanding context entails which of the following?
  • Breaking things down into smaller steps or pieces
  • Managing people, processes, and tools
  • Balancing roles and responsibilities
  • Understanding the condition in which something exists or happens

 

  1. Fill in the blank: _____ involves the ability to break things down into smaller steps or pieces and work with them in an orderly and logical way.
  • Data strategy
  • Curiosity
  • Context
  • A technical mindset

 

  1. Which analytical skill involves managing the people, processes, and tools used in data analysis?
  • Understanding context
  • Data design
  • Data strategy
  • Curiosity

 

  1. The manager at a music shop notices that more trombones are repaired on the days when Alex and Jasmine work the same shift. After some investigation, the manager discovers that Alex is excellent at fixing slides, and Jasmine is great at shaping mouthpieces. Working together, Alex and Jasmine repair trombones faster. The manager is happy to have discovered this relationship and decides to always schedule Alex and Jasmine for the same shifts. In this scenario, the manager used which quality of analytical thinking?
  • Visualization
  • Problem-orientation
  • Correlation
  • Big-picture thinking

 

  1. Fill in the blank: In order to get to the root cause of a problem, a data analyst should ask “Why?” ________ times.
  • five
  • three
  • seven
  • four

 

  1. A company is receiving negative comments on social media about their products. To solve this problem, a data analyst uses each of their five analytical skills: curiosity, understanding context, having a technical mindset, data design, and data strategy. This makes it possible for the analyst to use facts to guide business strategy and figure out how to improve customer satisfaction. What is this an example of?
  • Data science
  • Gap analysis
  • Data-driven decision-making
  • Data visualization

 

  1. Data analysts following data-driven decision-making use the analytical skills of curiosity, having a technical mindset, and data design. What other two analytical skills would they employ? Select all that apply.
  • knowledge
  • data strategy
  • efficiency
  • understanding context

 

  1. Curiosity is the analytical skill of using your instinct to solve problems.
  • True
  • False

 

  1. Adding descriptive headers to columns of data in a spreadsheet is an example of which analytical skill?
  • Having a technical mindset
  • Understanding context
  • Data strategy
  • Curiosity

 

  1. A company has recently tasked their data science team with figuring out what is causing the decline in production at one of their plants. The data analysts ask a number of questions trying to get to the root cause of the problem. This technique is known as what?
  • Inquiry
  • The five whys
  • Curiosity
  • Strategizing

 

Week 3 – The wonderful world of data

 

A business analyst recently completed a project that their company has decided to use to solve a larger business problem. What step is this in the data analysis process?

  • Process
    • Analyze
  • Act
  • Share

 

A set of instructions used to perform a specified calculation is known as what?

  • A particular value
    • A function
    • A predefined statement
  • A formula

 

Which of the following is an example of why a data analyst may generate a query?

  • Visualizing data
  • Requesting data
  • Collecting data
  • Recording data

 

  1. Fill in the blank: A business decides what kind of data it needs, how the data will be managed, and who will be responsible for it during the _____ stage of the data life
  • analyze
  • manage
  • plan
  • capture

 

  1. The destroy stage of the data life cycle might involve which of the following actions? Select all that apply.
  • Storing data for future use
  • Shredding paper files
  • Uploading data to the cloud
  • Using data-erasure software

 

  1. During the capture stage of the data life cycle, a data analyst may use spreadsheets to aggregate data.
  • True
  • False

 

  1. Describe how the data life cycle differs from data analysis.
  • The data life cycle deals with making informed decisions; data analysis is using tools to transform data.
  • The data life cycle deals with transforming and verifying data; data analysis is using the insights gained from the data.
  • The data life cycle deals with identifying the best data to solve a problem; data analysis is about asking effective questions.
  • The data life cycle deals with the stages that data goes through during its useful life; data analysis is the process of analyzing data.

 

  1. What actions might a data analytics team take in the act phase of the data analysis process? Select all that apply.
  • Sharing analysis results using data visualizations
  • Putting a plan into action to help solve the business problem
  • Validating insights provided by analysts
  • Finalizing a strategy based on the analysis

 

  1. Fill in the blank: A formula is a set of instructions used to perform a specified calculation; whereas a function is _____.
  • a predefined operation
  • a question written by the user
  • a particular value
  • a computer programming language

 

  1. Fill in the blank: To request, retrieve, and update information in a database, data analysts use a ____.
  • calculation
  • dashboard
  • query
  • formula

 

  1. Structured query language (SQL) enables data analysts to communicate with a database.
  • True
  • False

 

Shuffle Q/A

  1. You are in the plan stage of the data lifecycle for your current project. What action might you take during this stage?
  • Decide what kind of data is needed.
  • Use a formula to perform calculations.
  • Validate insights provided by analysts.
  • Shred paper files.

 

  1. A data analyst is working at a small tech startup. They’ve just completed an analysis project, which involved private company information about a new product launch. In order to keep the information safe, the analyst uses secure data-erasure software for the digital files and a shredder for the paper files. Which state of the data life cycle does this describe?
  • Manage
  • Archive
  • Destroy
  • Plan

 

  1. A data analyst is working at a small tech startup. On their current project they are in the analyze stage of the data life cycle. What might they do in this stage?
  • Choose the format of their spreadsheet headings
  • Determine who is responsible for managing the data
  • Validate the insights provided by analysts
  • Use a formula to perform calculations

 

  1. Fill in the blank: Data analysis has six process steps whereas the data life cycle has six _____.
  • data analytics tools
  • steps
  • stages
  • key questions

 

  1. What is the main difference between a formula and a function?
  • A formula can be used multiple times in a spreadsheet; a function can only be used once.
  • A formula begins with an equal sign (=); a function begins with an asterisk (*).
  • A formula is a set of instructions used to perform a specified calculation; a function is a preset command that automatically performs a specified process.
  • A formula is used to add or subtract; a function is used to multiply or divide.

 

  1. What does a data analyst use to request information within a database?
  • Calculation
  • Dashboard
  • Formula
  • Query

 

  1. Why is SQL the most popular structured query language? Select all that apply.
  • SQL allows data analysts to use spreadsheets
  • SQL is the most secure database on the market
  • SQL is easy to understand
  • SQL works with a wide variety of databases

 

  1. A data analyst uses spreadsheets to aggregate data during the capture phase of the data life cycle.
  • True
  • False

 

  1. Fill in the blank: The data life cycle has six _____ .
  • data analytics tools
  • process steps
  • key questions
  • stages

 

  1. Fill in the blank: A query is used to _____ information from a database. Select all that apply.
  • request
  • retrieve
  • visualize
  • update

 

  1. Structured query language (SQL) allows a data analyst to retrieve and request data from a database. What else is SQL used for?
  • Visualizing data within a database
  • The revising phase of the data life cycle
  • Updating databases
  • The sharing phase of the data life cycle

 

  1. Fill in the blank: A business is determining who should be responsible for the data in their current data analysis project. This means that the company is in the ______ stage of the data life cycle.
  • manage
  • plan
  • analyze
  • capture

 

  1. Fill in the blank: Shredding paper files and using data-erasure software would be actions taken by a data analyst in the _________ stage of the data lifecycle.
  • Manage
  • Plan
  • Archive
  • Destroy

 

  1. Fill in the blank: Data analysis has six parts that are divided into distinct _____.
  • process steps
  • key questions
  • data analytics tools
  • stages

 

  1. Fill in the blank: In the _____ phase of the data analysis process, a data analytics team might validate the insights provided by analysts.
  • process
  • share
  • analyze
  • act

 

  1. In data analysis, a predefined operation is known as what?
  • A function
  • A formula
  • A particular value
  • A predefined statement

 

  1. In the course of their current project, a data analyst uses a query to retrieve and request information. Which of the following is a third option they can use a query for?
  • Visualizing data
  • Updating data
  • Deleting data
  • Collecting data

 

  1. In which stage of the data life cycle does a business decide what kind of data it needs, how the data will be managed, and who will be responsible for it?
  • Manage
  • Plan
  • Capture
  • Analyze

 

  1. A company takes the insights provided by its data analytics team, validates them, and finalizes a strategy. They then implement a plan to solve the original business problem. This describes the share step of the data analysis process.
  • True
  • False

 

  1. In the course of their current project, a data analyst uses a query to retrieve and request information. Which of the following are options the analyst can use a query for? Select all that apply.
  • Updating data
  • Collecting data
  • Visualizing data
  • Deleting data

 

  1. In the plan stage of the data life cycle, what decisions would a data analyst make? Select all that apply.
  • Who will be responsible for the data
  • How the data will be managed
  • What kind of data is needed
  • How the data will be analyzed

 

  1. In the analyze phase of the data life cycle, what might a data analyst do? Select all that apply.
  • Use spreadsheets to aggregate data
  • Use a formula to perform calculations
  • Create a report from their data
  • Chooses the format of their spreadsheet headings

 

  1. Fill in the blank: In the act phase of the data analysis process, a company may need to _____ the insights of the data analysis team.
  • accomplish
  • revise
  • validate
  • calculate

 

  1. In data analysis, a function is a predefined operation whereas a formula is a set of instructions used to carry out a specific calculation.
  • True
  • False

 

  1. A data analyst has finished an analysis project that involved private company data. They erase the digital files in order to keep the information secure. This describes which stage of the data life cycle?
  • Plan
  • Destroy
  • Archive
  • Manage

 

  1. Fill in the blank: Using a formula to perform calculations, creating a report from their data, and using spreadsheets to aggregate data would all be actions carried out in the ________ stage of the data lifecycle.
  • manage
  • plan
  • analyze
  • capture

 

  1. Fill in the blank: In the _____ phase of the data analysis process, a data analytics team might validate the insights provided by analysts.
  • process
  • act
  • analyze
  • share

 

  1. Fill in the blank: Structured query language (SQL) enables data analysts to _____ information from a database. Select all that apply.
  • retrieve
  • visualize
  • request
  • update

 

Week 4 – Set up your toolbox

 

You are working with a database table named employee that contains data about employees. You want to review all the columns in the table.

You write the SQL query below. Add a FROM clause that will retrieve the data from the employee table.

SELECT

*

FROM employee

What employee has the job title of Sales Manager?

  • Margaret Park
    • Andrew Adams
  • Nancy Edwards
  • Michael Mitchell

 

A data analyst creates the following visualization to clearly demonstrate how much more populous Charlotte is than the next-largest North Carolina city, Raleigh. What type of chart do they use?

  • A line chart
  • A column, or bar, chart
  • A scatter chart
  • A pie chart

 

Fill in the blank: A data analyst has to demonstrate how the population in a city has increased over time. In particular, they want to be able to see when the population has exceeded certain thresholds. The chart that would work best for this is a/an _____ chart.

  • area
  • line
  • column
  • bar

 

  1. In the following spreadsheet, the column labels in row 1 are called what?
  • Criteria
  • Attributes
  • Descriptors
  • Characteristics

 

 

  1. Fill in the blank: In row 8 of the following spreadsheet, you can find the _____ of Cary.
  • format
  • attribute
  • criteria
  • observation

 

 

  1. Fill in the blank: In the following spreadsheet, the _____ feature was used to alphabetize the city names in column B.
  • Organize range
  • Name range
  • Randomize range
  • Sort range

 

 

 

  1. A data analyst types =POPULATION(C2:C11) to find the average population of the cities in this spreadsheet. However, they realize they used the wrong formula. What syntax will correct this function?
  • =AVERAGE(C2-C11)
  • AVERAGE(C2:C11)
  • AVERAGE(C2-C11)
  • =AVERAGE(C2:C11)

 

 

  1. You are working with a database table named genre that contains data about music genres. You want to review all the columns in the table.

 

You write the SQL query below. Add a FROM clause that will retrieve the data from the genre table.

What is the name of the genre with ID number 3?

  • Jazz
  • Rock
  • Metal
  • Blues

 

 

  1. You are working with a database table that contains invoice data. The customer_id column lists the ID number for each customer. You are interested in invoice data for the customer with ID number 35.

You write the SQL query below. Add a WHERE clause that will return only data about the customer with ID number 35.

After you run your query, use the slider to view all the data presented.

What is the billing country for the customer with ID number 35?

  • Ireland
  • Argentina
  • Portugal
  • India

 

  1. A data analyst creates the following visualization to clearly demonstrate how much more populous Charlotte is than the next-largest North Carolina city, Raleigh. What type of chart is it?
  • A scatter chart
  • A column, or bar, chart
  • A line chart
  • A pie chart

 

 

  1. A data analyst wants to demonstrate a trend of how something has changed over time. What type of chart is best for this task?
  • Area
  • Column
  • Line
  • Bar

 

Shuffle Q/A

  1. Fill in the blank: In row 1 of the following spreadsheet, the words rank and name are called _____?
  • attributes
  • characteristics
  • criteria
  • descriptors

 

  1. In the following spreadsheet, where can you find all of the attributes—also known as the observation—of Fayetteville?
  • Row 7
  • Column B
  • Row 6
  • Cell B7

 

  1. Fill in the blank: In the following spreadsheet, the feature sort range can be used to ________ the city names in column B?
  • change
  • alphabetize
  • randomize
  • delete

 

  1. The function =AVERAGE(C2:C11) can be used to do what for the following spreadsheet?
  • Arrange the rows according to increasing population size.
  • Find the city with the largest population.
  • Arrange the rows according to decreasing population size.
  • Find the average population of the cities

 

  1. You are working with a database table named employee that contains data about employees. You want to review all the columns in the table.

 

You write the SQL query below. Add a FROM clause that will retrieve the data from the employee table.

What employee has the job title of Sales Manager?

  • Nancy Edwards
  • Margaret Park
  • Michael Mitchell
  • Andrew Adams

 

  1. You are working with a database table that contains invoice data. The customer_id column lists the ID number for each customer. You are interested in invoice data for the customer with ID number 40.

 

You write the SQL query below. Add a WHERE clause that will return only data about the customer with ID number 40.

After you run your query, use the slider to view all the data presented.

 

What is the billing city for the customer with ID number 40?

  • Paris
  • Dijon
  • London
  • Buenos Aires

 

  1. A data analyst has to create a visualization that makes it easy to show which of the top ten most populous cities in North Carolina have a population below 250,000 people. What type of chart would be best for this visualization?
  • Line chart
  • Pie chart
  • Bar chart
  • Scatter chart

 

  1. A data analyst wants to demonstrate how the population in Charlotte has increased over time. They create this data visualization. This is an example of an area chart.
  • True
  • False

 

  1. In row 1 of the following spreadsheet, the words rank, name, population, and county are called what?
  • Attributes
  • Descriptors
  • Criteria
  • Characteristics

 

  1. In the following spreadsheet, what feature was used to alphabetize the city names in column B?
  • Organize range
  • Sort range
  • Name range
  • Randomize range

 

  1. To find the average population of the cities in this spreadsheet, you type =AVERAGE. What is the proper way to type the range that will complete your function?

 

  • (C2,C11)
  • (C2-C11)
  • (C2:C11)
  • (C2*C11)

 

  1. You are working with a database table named playlist that contains data about playlists for different types of digital media. You want to review all the columns in the table.

 

You write the SQL query below. Add a FROM clause that will retrieve the data from the playlist table.

What is the playlist with ID number 3?

  • Audiobooks
  • Music
  • Movies
  • TV Shows

 

  1. You are working with a database table that contains invoice data. The customer_id column lists the ID number for each customer. You are interested in invoice data for the customer with ID number 28.

 

You write the SQL query below. Add a WHERE clause that will return only data about the customer with ID number 28.

After you run your query, use the slider to view all the data presented.

 

What is the billing city for the customer with ID number 28?

  • Bangalore
  • Buenos Aires
  • Dijon
  • Salt Lake City

 

  1. Which of the following best describes a bar chart?
  • It is a visualization that uses a circle which is divided into wedges sized based on numerical proportion.
  • It is a visualization that plots a sequence of points and connects them with them with straight lines or curves.
  • It is a visualization that represents data with columns, or bars, the heights of which are proportional to the values that they represent.
  • It is a visualization that plots individual points in the Cartesian coordinate plane.

 

  1. A data analyst has to create a visualization that clearly shows when and for how long the population of Charlotte has been above one million people. They choose to use a line chart. Why is this the best choice for their visualization?
  • It is a visualization that plots a sequence of points and connects them with straight lines or curves.
  • It is a visualization that uses a circle which is divided into wedges sized based on numerical proportion.
  • It is a visualization that represents data with columns, or bars, the heights of which are proportional to the values that they represent.
  • It is a visualization that plots individual points in the Cartesian coordinate plane.

 

  1. The words rank, name, population, and county in row 1 of the following spreadsheet are known as descriptors.
  • True
  • False

 

  1. Fill in the blank: In the following spreadsheet, the ________ of High Point describes all of the data in row 10.
  • criteria
  • dataset
  • observation
  • format

 

  1. If a data analyst wants to list the cities in this spreadsheet alphabetically, instead of numerically, what feature can they use in column B?
  • Sort range
  • Name range
  • Randomize range
  • Organize range

 

  1. A data analyst wants to create a visualization that depicts the populations of the top ten most populous cities in North Carolina. What type of chart would be best for this?
  • A pie chart
  • A scatter chart
  • A column, or bar, chart
  • A line chart

 

  1. A data analyst has to demonstrate a trend of how something has changed over time. What type of chart is best for this task?
  • Line
  • Area
  • Bar
  • Column

 

  1. You are working with a database table that contains invoice data. The customer_id column lists the ID number for each customer. You are interested in invoice data for the customer with ID number 54.

 

You write the SQL query below. Add a WHERE clause that will return only data about the customer with ID number 54.

After you run your query, use the slider to view all the data presented.

 

What is the billing address for the customer with ID number 54?

  • 1033 N Park Ave
  • 230 Elgin St
  • 110 Raeburn Pl
  • 801 W 4th St

 

  1. Fill in the blank: A data analyst creates a table, but they realize this isn’t the best visualization for their data. To fix the problem, they decide to use the ____ feature to change it to a column chart.
  • chart editor
  • rename
  • filter view
  • image

 

  1. You are working with a database table named employee that contains data about employees. You want to review all the columns in the table.

 

You write the SQL query below. Add a FROM clause that will retrieve the data from the employee table.

What is the job title of Andrew Adams?

  • General Manager
  • Sales Manager
  • Sales Support Agent
  • IT Manager

 

  1. Fill in the blank: Suppose you wanted to determine the average population of the cities in the following spreadsheet. The correct function syntax to use would be ________ .
  • =AVERAGE(C2-C11)
  • AVERAGE(D2:D11)
  • AVERAGE(C2:C11)
  • =AVERAGE(C2:C11)

 

Week 5 – Endless career possibilities

 

A college IT department needs to reduce the number of computers on campus for student use. How could a data analyst help identify a solution to this problem?

  • Analyze the number of classes schedules across all classrooms
  • Analyze the utilization of the computer labs on campus
  • Analyze data on the number of students enrolled
  • Analyze the square footage of all computer labs on campus

 

In data analytics, what is the term for an obstacle to be solved?

  • Issue
    • Question
  • Problem
  • Solution

 

  1. An online gardening magazine wants to understand why its subscriber numbers have been increasing. A data analyst discovers that significantly more people subscribe when the magazine has its annual 50%-off sale. This is an example of what?
  • Analyzing consumer preferences using artificial intelligence
  • Analyzing customer buying behaviors
  • Analyzing social media engagement
  • Analyzing the number of customers by calculating daily foot traffic

 

  1. Fill in the blank: A doctor’s office has discovered that patients are waiting 20 minutes longer for their appointments than in past years. To help solve this problem, a data analyst could investigate how many nurses are on staff at a given time compared to the number of _____.
  • doctors seeing new patients
  • patients with appointments
  • negative comments about the wait times on social media
  • doctors on staff at the same time

 

  1. A problem is an obstacle to be solved, an issue is a topic to investigate, and a question is designed to discover information.
  • True
  • False

 

  1. What is a question or problem that a data analyst answers for a business?
  • Mission statement
  • Hypothesis
  • Complaint
  • Business task

 

  1. Fill in the blank: Data-driven decision-making is described as using _____ to guide business strategy.
  • gut instinct
  • visualizations
  • facts
  • intuition

 

  1. It’s possible for conclusions drawn from data analysis to be both true and unfair.
  • True
  • False

 

  1. A data analyst is analyzing fruit and vegetable sales at a grocery store. They’re able to find data on everything except red onions. What’s the best course of action?
  • Ask a teammate for help finding data on red onions.
  • Exclude red onions from the analysis.
  • Exclude all onion varieties from the analysis.
  • Use the data on white onions instead, as they’re both onion varieties.

 

 

  1. Collaborating with a social scientist to provide insights into human bias and social contexts is an effective way to avoid bias in your data.
  • True
  • False

 

 

Shuffle Q/A

  1. A restaurant hires a data analyst to determine the best times to have the restaurant open. Which of the following methods can the data analyst use to help build a better schedule for the restaurant? Select all that apply.
  • Analyze weekly weather data
  • Analyze staffing levels for different days
  • Examine hourly customer numbers
  • Survey customers on their preferred times to dine

 

  1. A restaurant has noticed that customers often wait longer in line than in previous years. How could a data analyst help solve this problem?
  • Analyze the average sales amount per customer
  • Analyze customer survey results about the preferred opening hours of the restaurant
  • Analyze the number of staff on shift at any time
  • Analyze the products customers are purchasing

 

  1. Fill in the blank: A business task is described as the _____ a data analyst answers for a business.
  • solution
  • complaint
  • question
  • comment

 

  1. When you make decisions using observation and intuition as a guide, you only see part of the picture. What can improve your decision-making?
  • Using data
  • Using assumptions
  • Creating surveys
  • Being decisive

 

  1. Data analysts ensure their analysis is fair for what reason?
  • Fairness helps them avoid biased conclusions.
  • Fairness helps them stay organized.
  • Fairness helps them communicate with stakeholders.
  • Fairness helps them pick and choose which data to include from a dataset.

 

  1. A large hotel chain sees about 500 customers per week. A data analyst working there is gathering data through customer satisfaction surveys. They are anxious to begin analysis, so they start analyzing the data as soon as they receive 50 survey responses. This is an example of what? Select all that apply.
  • Failing to include diverse perspectives in data collection
  • Failing to collect data anonymously
  • Failing to reward customers for participating in the survey
  • Failing to have a large enough sample size

 

  1. An online gardening magazine wants to understand why its subscriber numbers have been increasing. What kind of reports can a data analyst provide to help answer that question? Select all that apply.
  • Reports that describe how many customers shared positive comments about the gardening magazine on social media in the past year
  • Reports that predict the success of sales leads to secure future subscribers
  • Reports that examine how a recent 50%-off sale affected the number of subscription purchases
  • Reports that compare past weather patterns to the number of people asking gardening questions to their social media

 

  1. Fill in the blank: In data analytics, a question is _____.
  • an obstacle or complication that needs to be worked out
  • a way to discover information
  • a topic to investigate
  • a subject to analyze

 

  1. What must a data analyst establish before they can start to plan the best approach to gather and analyze information?
  • The business task
  • The statement
  • The complaint
  • The solution

 

  1. What is the process of using facts to guide business strategy?
  • Data-driven decision-making
  • Data ethics
  • Data visualization
  • Data programming

 

  1. A data analyst is developing a model. They start by gathering data for groups that are underrepresented in a sample. What strategy could they employ to ensure these groups are represented fairly?
  • Oversample the underrepresented group
  • Sample the underrepresented group normally
  • Combine the underrepresented group with another group
  • Exclude the underrepresented group from the sample

 

  1. A restaurant is trying to develop more effective staffing strategies. A data analyst recognizes that there are significantly fewer customers earlier in the business day. They conclude that opening later would be more effective for staffing. What is this an example of?
  • Creating efficiencies by analyzing customer foot traffic
  • Tailoring products to consumer buying habits
  • Creating more effective customer communication
  • Gathering customer opinions about business changes

 

  1. A restaurant has noticed many popular dishes are running out early in the day. How could a data analyst help identify a solution to this problem? Select all that apply.
  • Analyze ordering patterns of those products
  • Examine the number of sales of those products
  • Examine overall daily sales of the restaurant
  • Analyze the number of staff on shift during peak times

 

  1. When working for a restaurant, a data analyst is asked to examine and report on the daily sales data from year to year to help with making more efficient staffing decisions. What is this an example of?
  • A business task
  • An issue
  • A solution
  • A breakthrough

 

  1. Data-driven decision-making is using facts to guide business strategy. The benefits include which of the following? Select all that apply.
  • Getting a complete picture of a problem and its causes
  • Combining observation with objective data
  • Using data analytics to find the best possible solution to a problem
  • Making the most of intuition and gut instinct

 

  1. A data analyst is analyzing fruit and vegetable sales at a grocery store. They’re able to find data on everything except red onions. If they exclude red onions from the analysis, this would be an example of creating or reinforcing bias.
  • True
  • False

 

  1. A hotel is trying to gather data on their guests' satisfaction with their stay. Which of the following options would best help the hotel account for potential bias in their data?
  • Surveying guests at random times throughout the year
  • Only surveying guests who have booked their stay through a certain third-party website
  • Only surveying guests who have stayed at the hotel during peak season
  • Only surveying guests who have stayed at the hotel for more than 3 nights

 

  1. A restaurant is struggling to accurately staff for the different daily customer volumes. On some days, there are many servers and few customers. On other days, the restaurant is very busy and there are not enough servers and kitchen staff. What reports could a data analyst use to create more efficient staffing strategies? Select all that apply.
  • Reports of past and future reservations
  • Reports of past weather patterns in the area of the restaurant
  • Reports using historical sales data to predict sales for the current day/date
  • Reports of planned local events in the area of the restaurant

 

  1. Fill in the blank: In data analytics, a topic to investigate is also known as a(n) _____.
  • theme
  • issue
  • question
  • statement

 

  1. When a choice is made between good, bad, or a combination of consequences based on facts, it is also known as what?
  • Data-driven decision-making
  • Data ethics
  • Data visualization
  • Data programming

 

  1. At what point in the data analysis process should a data analyst consider fairness?
  • When decisions are made based on the conclusions
  • When data collection begins
  • When data is being organized for reporting
  • When conclusions are presented

 

  1. A restaurant is considering changing their operating hours. They survey customers that come in between 4 p.m. and 5 p.m. to get feedback on this potential change. What can the restaurant do to ensure the data analysis process is fair?
  • Expand the times when they survey customers
  • Survey only repeat customers
  • Reward customers for participating in the survey
  • Survey people walking by on the street

 

  1. A doctor’s office discovers that patients are waiting 20 minutes longer for their appointments than in past years. In what ways could a data analyst help solve this problem? Select all that apply.
  • Analyze the average length of an appointment this year compared to past years.
  • Analyze the number of patients seen per day compared to past years.
  • Analyze a recent change in the average rating for the doctor’s office on social media.
  • Analyze how many doctors and nurses are on staff at a given time compared to the number of patients with appointments

 

  1. Fill in the blank: Fairness is achieved when data analysis doesn’t create or _____ bias.
  • reinforce
  • constrain
  • highlight
  • resolve

 

  1. A gym wants to start offering exercise classes. A data analyst plans to survey 10 people to determine which classes would be most popular. To ensure the data collected is fair, what steps should they take? Select all that apply.
  • Ensure participants represent a variety of profiles and backgrounds.
  • Collect data anonymously.
  • Survey only people who don’t currently go to the gym.
  • Increase the number of participants.

 

  1. A doctor’s office has discovered that patients are waiting 20 minutes longer for their appointments than in past years. A data analyst could help solve this problem by analyzing how many doctors and nurses are on staff at a given time compared to the number of patients with appointments.
  • True
  • False

 

  1. Fill in the blank: Once an analyst has identified a problem for a business, they establish a(n)_____ to help inform the process of gathering the correct information.
  • issue
  • business task
  • statement
  • solution

 

  1. Which of the following best describes what fairness in data analytics means?
  • Ensuring that analysis does not create or reinforce bias
  • Including data from dominant groups
  • Collecting data objectively
  • Including self-reported data

 

Course Challenge

 

Scenario 1, question 1-5

You’ve just started a new job as a data analyst for a midsized pharmacy chain with 38 stores in the American Southwest. Your supervisor shares a new data analysis project with you.

She explains that the pharmacy is considering discontinuing a bubble bath product called Splashtastic. Your supervisor wants you to analyze sales data and determine what percentage of each store’s total daily sales come from that product. Then, you’ll present your findings to leadership.

You know that it's important to follow each step of the data analysis process: ask, prepare, process, analyze, share, and act. So, you begin by defining the problem and making sure you fully understand stakeholder expectations.

One of the questions you ask is where to find the dataset you’ll be working with. Your supervisor explains that the company database has all the information you need.

Next, you continue to the prepare step. You access the database and write a query to retrieve data about Splashtastic. You notice that there are only 38 rows of data, representing the company’s 38 stores. In addition, your dataset contains five columns: Store Number, Average Daily Customers, Average Daily Splashtastic Sales (Units), Average Daily Splashtastic Sales (Dollars), and Average Total Daily Sales (All Products). You decide to use a spreadsheet to work with the data because you know that spreadsheets work well for processing and analyzing a small dataset, like the one you’re using.

Fill in the blank: To get the data from the database into a spreadsheet, you would first _____ the data as a .CSV file, then import it into a spreadsheet.

  • email
  • download
  • copy and paste
  • print

 

Scenario 1 continued

You’ve downloaded the data from your company database and imported it into a spreadsheet. IMPORTANT: To answer questions using this dataset for the scenario, click the link below and select the “Use Template” button before answering the questions.

Link to template: Course Challenge - Scenario 1

OR

If you don’t have a Google account, you can download the template directly from the attachment below.

Course Challenge Dataset - Scenario 1 - Scenario 1_ Pharmacy Data - Part 1

CSV File

Now, it’s time to process the data. As you know, this step involves finding and eliminating errors and inaccuracies that can get in the way of your results. While cleaning the data, you notice that information about Splashtastic is missing for Store Number 15 in Row 16. Which of the following would be an appropriate course of action?

  • Delete the row with the missing data point.
    • Replace the row with the average values of the other data points.
    • Sort the spreadsheet so the row with missing data is at the bottom.
  • Investigate previous projects and see how this was dealt with there.

 

Scenario 1 continued

Once you’ve found the missing information, you analyze your dataset.

During analysis, you create a new column F. At the top of the column, you add: Average Percentage of Total Sales - Splashtastic. What is this column label called?

  • A title
    • A reference
  • An attribute
  • A headline

 

Scenario 1 continued

Next, you determine the average total daily sales over the past 12 months at all stores. The entire range of cells that contain these sales are E2:E39. The correct syntax is =AVERAGE(E2:E39).

  • True
  • False

 

Scenario 1 continued

Fill in the blank: You’ve reached the share phase of the data analysis process. One of the things that you can do in this phase is to prepare a _____ about Splashtastic’s sales and practice your presentation.

  • prediction
    • finding
    • record
  • slideshow

Scenario 2, questions 6-10

You’ve been working for the nonprofit National Dental Society (NDS) as a junior data analyst for about two months. The mission of the NDS is to help its members advance the oral health of their patients. NDS members include dentists, hygienists, and dental office support staff.

The NDS is passionate about patient health. Part of this involves automatically scheduling follow-up appointments after crown replacement, emergency dental surgery, and extraction procedures. NDS believes the follow-up is an important step to ensure patient recovery and minimize infection.

Unfortunately, many patients don’t show up for these appointments, so the NDS wants to create a campaign to help its members learn how to encourage their patients to take follow-up appointments seriously. If successful, this will help the NDS achieve its mission of advancing the oral health of all patients.

Your supervisor has just sent you an email saying that you’re doing very well on the team, and he wants to give you some additional responsibility. He describes the issue of many missed follow-up appointments. You are tasked with analyzing data about this problem and presenting your findings using data visualizations.

An NDS member with three dental offices in Colorado offers to share its data on missed appointments. So, your supervisor uses a database query to access the dataset from the dental group. The query instructs the database to retrieve all patient information from the member’s three dental offices, located in zip code 81137.

The table is dental_data_table, and the column name is zip_code. You write the following query, but get an error. What statement will correct the problem?

SELECT * FROM dental_data_table WHERE zip code = 81137

  • zip_code = 81137
    • WHERE_zip code = 81137
  • WHERE zip_code = 81137
  • WHERE 81137

 

Scenario 2 continued

The dataset your supervisor retrieved and imported into a spreadsheet includes a list of patients, their demographic information, dental procedure types, and whether they attended their follow-up appointment. To use the dataset for this scenario, click the link below and select “Use Template.”

Link to template: Course Challenge - Scenario 2

OR

If you don’t have a Google account, you can download the template directly from the attachment below.

Course Challenge Dataset - Scenario 2

CSV File

The patient demographic information includes data such as age, gender, and home address. When examining the geographic data, you notice that all the patients live in the same zip code.

Fill in the blank: The fact that the dataset includes people who all live in the same zip code might get in the way of ______.

  • fairness
  • accuracy
  • spreadsheet formulas or functions
  • data visualization

 

Scenario 2 continued

As you’re reviewing the dataset, you notice that there are a disproportionate number of senior citizens. So, you investigate further and find out that this zip code represents a rural community in Colorado with about 800 residents. In addition, there’s a large assisted-living facility in the area. Nearly 300 of the residents in the 81137 zip code live in the facility.

You recognize that’s a sizable number, so you want to find out if age has an effect on a patient’s likelihood to attend a follow-up dental appointment. You analyze the data, and your analysis reveals that older people tend to miss follow-ups more than younger people.

So, you do some research online and discover that people over the age 60 are 50% more likely to miss dentist appointments. Sometimes this is because they’re on a fixed income. Also, many senior citizens lack transportation to get to and from appointments.

With this new knowledge, you write an email to your supervisor expressing your concerns about the dataset. He agrees with your concerns, but he’s also impressed with what you’ve learned and thinks your findings could be very important to the project. He asks you to change the business task. Now, the NDS campaign will be about educating dental offices on the challenges faced by senior citizens and finding ways to help them access quality dental care.

Fill in the blank: Changing the business task involves defining a new _____.

  • gap analysis plan
    • graphical representation of the data
  • question or problem to be solved
  • data-cleaning strategy

 

Scenario 2 continued

You continue with your analysis. In the end, your findings support what you discovered during your online research: As people get older, they’re less likely to attend follow-up dental visits.

But you’re not done yet. You know that data should be combined with human insights in order to lead to true data-driven decision-making. So, your next step is to share this information with people who are familiar with the problem professionally. They’ll help verify the results of your data analysis.

Fill in the blank: The people who are familiar with a problem and help verify the results of data analysis are _____.

  • customers
    • data scientists
    • stakeholders
  • subject-matter experts

 

Scenario 2 continued

The subject-matter experts are impressed by your analysis. The team agrees to move to the next step: data visualization. You know it’s important that stakeholders at NDS can quickly and easily understand that older people are less likely to attend important follow-up dental appointments than younger people. This will help them create an effective campaign for members.

It’s time to create your presentation to stakeholders. It will include a data visualization that demonstrates the lifetime trend of people being less likely to attend follow-up appointments as they get older.

Why would a line chart be the most effective in representing this?

  • Line charts are effective in displaying points in series.
  • Line charts arrange data values into rows.
  • Line charts represent data values as proportionally sized wedges.
  • Line charts arrange data values into columns.

 

Scenario 1, question 1-5

You’ve just started a new job as a data analyst. You’re working for a midsized pharmacy chain with 38 stores in the American Southwest. Your supervisor shares a new data analysis project with you.She explains that the pharmacy is considering discontinuing a bubble bath product called Splashtastic. Your supervisor wants you to analyze sales data and determine what percentage of each store’s total daily sales come from that product. Then, you’ll present your findings to leadership.You know that it's important to follow each step of the data analysis process: ask, prepare, process, analyze, share, and act. So, you begin by defining the problem and making sure you fully understand stakeholder expectations.One of the questions you ask is where to find the dataset you’ll be working with. Your supervisor explains that the company database has all the information you need. Next, you continue to the prepare step. You access the database and write a query to retrieve data about Splashtastic. You notice that there are only 38 rows of data, representing the company’s 38 stores. In addition, your dataset contains five columns: Store Number, Average Daily Customers, Average Daily Splashtastic Sales (Units), Average Daily Splashtastic Sales (Dollars), and Average Total Daily Sales (All Products).

You know that spreadsheets work well for processing and analyzing a small dataset, like the one you’re using. To get the data from the database into a spreadsheet, what should you do?

  • Email a copy of the dataset to your company email address.
    • Use Tableau to convert the data into a spreadsheet.
  • Download the data as a .CSV file, then import it into a spreadsheet.
  • Copy and paste the data into a spreadsheet.

 

Scenario 1 continued

You’ve downloaded the data from your company database and imported it into a spreadsheet. IMPORTANT: To answer questions using this dataset for the scenario, click the link below and select the “Use Template” button before answering the questions.

Link to template: Course Challenge - Scenario 1

OR

If you don’t have a Google account, you can download the template directly from the attachment below.

Course Challenge Dataset - Scenario 1 - Scenario 1_ Pharmacy Data - Part 1

CSV File

Now, it’s time to process the data. As you know, this step involves finding and eliminating errors and inaccuracies that can get in the way of your results. While cleaning the data, you notice that information about Splashtastic is missing for Store Number 15 in Row 16. Which of the following would be an appropriate response?

  • Sort the spreadsheet so the row with missing data is at the bottom.
  • Ask a colleague on your team how they've handled similar issues in the past.
  • Delete the row with the missing data point.
  • Replace the row with the average values of the other data points.

 

Scenario 1 continued

Once you’ve found the missing information, you analyze your dataset. During analysis, you create a new column F. At the top of the column, you add the attribute Average Percentage of Total Sales - Splashtastic.

Fill in the blank: An attribute is a _______ or quality of data used to label a column.

  • number
    • headline
    • response
  • characteristic

 

Scenario 1 continued

Next, you determine the average total daily sales over the past 12 months at all stores. The entire range of cells that contain these sales are E2:E39. Identify the correct way to write your function.

  • =AVERAGE(E2+E39)
    • =AVERAGE(E2,E39)
  • =AVERAGE(E2:E39)
  • =AVERAGE(E2-E39)

 

Scenario 1 continued

You’ve reached the share phase of the data analysis process. It involves which of the following? Select all that apply.

  • Present your findings about Splashtastic to stakeholders.
  • Prepare a slideshow about Splashtastic’s sales and practice your presentation.
  • Create a data visualization to highlight the Splashtastic sales insights you've discovered.
  • Stop selling Splashtastic because it doesn't represent a large percentage of total sales.

 

Scenario 2, questions 6-10

You’ve been working for the nonprofit National Dental Society (NDS) as a junior data analyst for about two months. The mission of the NDS is to help its members advance the oral health of their patients. NDS members include dentists, hygienists, and dental office support staff.

The NDS is passionate about patient health. Part of this involves automatically scheduling follow-up appointments after crown replacement, emergency dental surgery, and extraction procedures. NDS believes the follow-up is an important step to ensure patient recovery and minimize infection.

Unfortunately, many patients don’t show up for these appointments, so the NDS wants to create a campaign to help its members learn how to encourage their patients to take follow-up appointments seriously. If successful, this will help the NDS achieve its mission of advancing the oral health of all patients.

Your supervisor has just sent you an email saying that you’re doing very well on the team, and he wants to give you some additional responsibility. He describes the issue of many missed follow-up appointments. You are tasked with analyzing data about this problem and presenting your findings using data visualizations.

An NDS member with three dental offices in Colorado offers to share its data on missed appointments. So, your supervisor uses a database query to access the dataset from the dental group. The query instructs the database to retrieve all patient information from the member’s three dental offices, located in zip code 81137.

The table is dental_data_table, and the column name is zip_code. You have written the following query, but received an error when it ran.

SELECT * FROM dental_data_table WHERE dental_data_table = 81137

Given the objective of the query, where is the mistake in this query?

  • SELECT, FROM, and WHERE should not be capitalized.
    • In line 2, dental_data_table should be replaced with zip_code 81137.
    • The third line should be WHERE = 81137
  • In line 3, dental_data_table should be replaced with zip_code.

 

Scenario 2 continued

The dataset your supervisor retrieved and imported into a spreadsheet includes a list of patients, their demographic information, dental procedure types, and whether they attended their follow-up appointment. To use the dataset for this scenario, click the link below and select “Use Template.”

Link to template: Course Challenge - Scenario 2

OR

If you don’t have a Google account, you can download the template directly from the attachment below.

Course Challenge Dataset - Scenario 2

CSV File

The patient demographic information includes data such as age, gender, and home address. When examining the geographic data, you notice that all the patients live in the same zip code.

Fill in the blank: The fact that the dataset includes people who all live in the same zip code might get in the way of ______.

  • fairness
  • accuracy
  • spreadsheet formulas or functions
  • data visualization

 

Scenario 2 continued

As you’re reviewing the dataset, you notice that there are a disproportionate number of senior citizens. So, you investigate further and find out that this zip code represents a rural community in Colorado with about 800 residents. In addition, there’s a large assisted-living facility in the area. Nearly 300 of the residents in the 81137 zip code live in the facility.

You recognize that’s a sizable number, so you want to find out if age has an effect on a patient’s likelihood to attend a follow-up dental appointment. You analyze the data, and your analysis reveals that older people tend to miss follow-ups more than younger people.

So, you do some research online and discover that people over the age 60 are 50% more likely to miss dentist appointments. Sometimes this is because they’re on a fixed income. Also, many senior citizens lack transportation to get to and from appointments.

With this new knowledge, you write an email to your supervisor expressing your concerns about the dataset. He agrees with your concerns, but he’s also impressed with what you’ve learned and thinks your findings could be very important to the project. He asks you to change the business task. Now, the NDS campaign will be about educating dental offices on the challenges faced by senior citizens and finding ways to help them access quality dental care.

The business task has changed. What is the nature of that change?

  • Creating a graphical representation of the data
    • Using a database instead of a spreadsheet
    • Conducting a gap analysis
  • Defining the new question or problem to be solved

 

Scenario 2 continued

You continue with your analysis. In the end, your findings support what you discovered during your online research: As people get older, they’re less likely to attend follow-up dental visits.

But you’re not done yet. You know that data should be combined with human insights in order to lead to true data-driven decision-making. So, your next step is to share this information with people who are familiar with the problem professionally. They’ll help verify the results of your data analysis.

Fill in the blank: The people who are familiar with a problem and help verify the results of data analysis are _____.

  • stakeholders
  • subject-matter experts
  • customers
  • data scientists

 

Scenario 2 continued

The subject-matter experts are impressed by your analysis. The team agrees to move to the next step: data visualization. You know it’s important that stakeholders at NDS can quickly and easily understand that older people are less likely to attend important follow-up dental appointments than younger people. This will help them create an effective campaign for members.

It’s time to create your presentation to stakeholders. It will include a data visualization that demonstrates the lifetime trend of people being less likely to attend follow-up appointments as they get older.

Which type of chart will be most effective?

  • A doughnut chart
    • A table
    • A pie chart
  • A line chart

 

Scenario 1 continued

You’ve downloaded the data from your company database and imported it into a spreadsheet. IMPORTANT: To answer questions using this dataset for the scenario, click the link below and select the “Use Template” button before answering the questions.

Link to template: Course Challenge - Scenario 1

OR

If you don’t have a Google account, you can download the template directly from the attachment below.

Course Challenge Dataset - Scenario 1 - Scenario 1_ Pharmacy Data - Part 1

CSV File

Now, it’s time to process the data. As you know, this step involves finding and eliminating errors and inaccuracies that can get in the way of your results. While cleaning the data, you notice there’s missing data in one of the rows. What might you do to fix this problem? Select all that apply.

  • Ask a colleague on your team how they've handled similar issues in the past
  • Sort the spreadsheet so the row with missing data is at the bottom
    • Delete the row with the missing data point
  • Ask you supervisor for guidance

 

Scenario 1 continued

Next, you determine the average total daily sales over the past 12 months at all stores. The entire range of cells that contain these sales are E2:E39. To do this, you use a function. You input =AVE(E2:E39), but this returns an error. What is the correct command?

  • =AVERAGE(E2:E39)
  • =AVERAGE(E2+E39)
  • =AVERAGE(E2,E29)
  • =AVERAGE(E2-E39)

 

Scenario 2, questions 6-10

You’ve been working for the nonprofit National Dental Society (NDS) as a junior data analyst for about two months. The mission of the NDS is to help its members advance the oral health of their patients. NDS members include dentists, hygienists, and dental office support staff.

The NDS is passionate about patient health. Part of this involves automatically scheduling follow-up appointments after crown replacement, emergency dental surgery, and extraction procedures. NDS believes the follow-up is an important step to ensure patient recovery and minimize infection.

Unfortunately, many patients don’t show up for these appointments, so the NDS wants to create a campaign to help its members learn how to encourage their patients to take follow-up appointments seriously. If successful, this will help the NDS achieve its mission of advancing the oral health of all patients.

Your supervisor has just sent you an email saying that you’re doing very well on the team, and he wants to give you some additional responsibility. He describes the issue of many missed follow-up appointments. You are tasked with analyzing data about this problem and presenting your findings using data visualizations.

An NDS member with three dental offices in Colorado offers to share its data on missed appointments. So, your supervisor uses a database query to access the dataset from the dental group. The query instructs the database to retrieve all patient information from the member’s three dental offices, located in zip code 81137.

The table is dental_data_table, and the column name is zip_code. You write the following query.

SELECT * FROM dental_data_table WHERE zip code = 81137

This query is incorrect. How could it be fixed?

  • In line 3, replace zip code with zip_code
  • Decapitalize SELECT, FROM, and WHERE
  • Rewrite line 3 as WHERE_zip code = 81137
  • Rewrite line 3 as zip_code = 81137

 

Scenario 2 continued

The dataset your supervisor retrieved and imported into a spreadsheet includes a list of patients, their demographic information, dental procedure types, and whether they attended their follow-up appointment. To use the dataset for this scenario, click the link below and select “Use Template.”

Link to template: Course Challenge - Scenario 2

OR

If you don’t have a Google account, you can download the template directly from the attachment below.

Course Challenge Dataset - Scenario 2

CSV File

The patient demographic information includes data such as age, gender, and home address. You review the demographic data, paying particular attention to geography. What geographic aspect of the data may negatively impact fairness?

  • The patients all live in the same city.
    • The patients all live in houses.
    • The patients all live in the same country.
  • The patients all live in the same zip code.

Scenario 2 continued

You continue with your analysis. In the end, your findings support what you discovered during your online research: As people get older, they’re less likely to attend follow-up dental visits.

But you’re not done yet. You know that data should be combined with human insights in order to lead to true data-driven decision-making. So, your next step is to share this information with people who are familiar with the problem professionally. They’ll help verify the results of your data analysis.

Fill in the blank: Subject matter experts are people who are familiar with a problem. They can help by identifying inconsistencies in the analysis, _____, and validating the choices being made.

  • redefining the business problem
  • offering insights into the business problem
  • creating a presentation with the data
  • collecting data relevant to the business problem

 

Scenario 2 continued

The subject-matter experts are impressed by your analysis. The team agrees to move to the next step: data visualization. You know it’s important that stakeholders at NDS can quickly and easily understand that older people are less likely to attend important follow-up dental appointments than younger people. This will help them create an effective campaign for members.

It’s time to create your presentation to stakeholders. It will include a data visualization that demonstrates the lifetime trend of people being less likely to attend follow-up appointments as they get older.

Fill in the blank: The type of chart that would be most effective in visualizing this is a _____.

  • bar chart
    • pie chart
    • doughnut chart
  • line chart

 

Course 2 – Ask Questions to Make Data-Driven Decisions

 

Week 1 – Effective questions

 

In structured thinking, why would a data analyst organize the available information?

  • To ask SMART questions
  • To recognize the current problem or situation
  • To summarize results using data visualizations
  • To consult with subject matter experts

 

A local internet service provider is expecting an increase in the number of people streaming online entertainment. Their data analyst uses data to estimate the required bandwidth necessary to service its customers. This is an example of which problem type?

  • Discovering connections
    • Identifying themes
  • Making predictions
  • Spotting something unusual

 

Fill in the blank: The question, “How could we improve our website to simplify the returns process for our online customers?” is _____-oriented.

  • action
  • bias
  • passive
  • data

 

  1. Structured thinking involves which of the following processes? Select all that apply.
  • Revealing gaps and opportunities
  • Recognizing the current problem or situation
  • Organizing available information
  • Asking SMART questions

 

  1. A data analyst creates data visualizations and a slideshow. Which phase of the data analysis process does this describe?
  • Prepare
  • Act
  • Share
  • Process

 

  1. A recycling center that sponsors a podcast about saving the environment is an example of what strategy?
  • Defining the problem to be solved
  • Making recommendations
  • Staying on budget
  • Trying to reach a target audience

 

  1. A data analyst is working for a local power company. Recently, many new apartments have been built in the community, so the company wants to determine how much electricity it needs to produce for the new residents in the future. A data analyst uses data to help the company make a more informed forecast. This is an example of which problem type?
  • Spotting something unusual
  • Discovering connections
  • Making predictions
  • Identifying themes

 

  1. Describe the key difference between the problem types of categorizing things and identifying themes.
  • Categorizing things involves determining how items are different from each other. Identifying themes brings different items back together in a single group.
  • Categorizing things involves assigning grades to items. Identifying themes involves creating new classifications for items.
  • Categorizing things involves taking inventory of items. Identifying themes deals with creating labels for items.
  • Categorizing things involves assigning items to categories. Identifying themes takes those categories a step further, grouping them into broader themes.

 

  1. Which of the following examples are leading questions? Select all that apply.
  • What do you enjoy most about our service?
  • How did you learn about our company?
  • In what ways did our product meet your needs?
  • How satisfied were you with our customer representative?

 

  1. The question, “Why don’t our employees complete their timesheets each Friday by noon?” is not action-oriented. Which of the following questions are action-oriented and more likely to lead to change? Select all that apply.
  • What functionalities would make our timesheet web page more user-friendly?
  • What features could we add to our calendar app as a weekly timesheet reminder to employees?
  • How could we simplify the time-keeping process for our employees?
  • Why don’t employees prioritize filling out their timesheets by noon on Fridays?

 

  1. On a customer service questionnaire, a data analyst asks, “If you could contact our customer service department via chat, how much valuable time would that save you?” Why is this question unfair?
  • It is closed-ended
  • It uses slang words that not everyone can understand
  • It is vague
  • It makes assumptions

 

 

Shuffle Q/A

  1. Organizing available information and revealing gaps and opportunities are part of what process?
  • Identifying connections between two or more things
  • Categorizing things
  • Using structured thinking
  • Applying the SMART methodology

 

  1. The share phase of the data analysis process typically involves which of the following activities? Select all that apply.
  • Summarizing results using data visualizations
  • Communicating findings
  • Creating a slideshow to present to stakeholders
  • Putting analysis into action to solve a problem

 

  1. A company wants to make more informed decisions regarding next year’s business strategy. An analyst uses data to help identify how things will likely work out in the future. This is an example of which problem type?
  • Making predictions
  • Spotting something unusual
  • Identifying themes
  • Discovering connections

 

  1. Fill in the blank: Categorizing things involves assigning items to categories, whereas _____ takes those categories a step further, grouping them into broader classifications.
  • Making predictions
  • Finding patterns
  • Discovering connections
  • Identifying themes

 

  1. Questions that make assumptions often involve concepts that are formed without evidence. An example of this is an idea that is accepted as true without proof.
  • True
  • False

 

  1. A garden center wants to attract more customers. A data analyst in the marketing department suggests advertising in popular landscaping magazines. This is an example of what practice?
  • Reaching your target audience
  • Collecting customer information
  • Monitoring social media feedback
  • Developing a data analytics case study

 

  1. Categorizing things involves assigning items to categories. Identifying themes takes those categories a step further, grouping them into broader themes or classifications.
  • True
  • False

 

  1. Which of the following examples are closed-ended questions? Select all that apply.
  • Is math your favorite subject?
  • What grade did you get on the math test?
  • How old are you?
  • What are your thoughts about math?

 

  1. The question, “How could we improve our website to simplify the returns process for our online customers?” is action-oriented.
  • True
  • False

 

  1. Which of the following questions make assumptions? Select all that apply.
  • Keeping employees engaged is important, isn’t it?
  • Wouldn’t you agree that product A is better than product B?
  • Did you get through to customer service?
  • It must be frustrating waiting on hold for so long, right?

 

  1. Structured thinking involves recognizing the current problem or situation you’re facing and identifying your options.
  • True
  • False

 

  1. Which of the following examples are leading questions? Select all that apply.
  • How satisfied were you with our customer representative?
  • What do you enjoy most about our service?
  • In what ways did our product meet your needs?
  • How did you learn about our company?

 

  1. On a customer service questionnaire, a data analyst asks, “If you could contact our customer service department via chat, how much valuable time would that save you?” Why is this question unfair?
  • It is closed-ended
  • It uses slang words that not everyone can understand
  • It is vague
  • It makes assumptions

 

  1. Fill in the blank: To apply structured thinking, a data analyst should ______ the available information in order to reveal gaps and opportunities and recognize the current problem or situation.
  • organize
  • communicate
  • share
  • record

 

  1. A national chain of sporting goods stores advertises during popular sporting television broadcasts. This is an example of the company doing what?
  • Reaching its target audience
  • Demonstrating its support for a sports team
  • Defining the problem to be solved
  • Monitoring social feedback

 

  1. In data analysis, categorizing things involves which of the following?
  • Creating new classifications for items and assigning grades to items
  • Assigning items to categories
  • Taking an inventory of items
  • Determining how items are different from each other

 

  1. The question, “Why was the Monday afternoon yoga class successful?” is not measurable. Which of the following questions presents a measurable way to learn about the yoga class?
  • Why do people like taking yoga classes on Mondays?
  • How many customers responded to our recent half-price yoga promotion?
  • Is yoga a great way to stretch and strengthen your body?
  • Do yoga instructors seem more energetic at the beginning of the week?

 

  1. Why should a data analyst only ask fair questions?
  • Unfair questions do not have answers.
  • Unfair questions can provide data that is misleading.
  • Fair questions are biased.
  • Fair questions do not offend people.

 

  1. In the share step of the data analysis process, a data analyst summarizes their results using data visualizations and creates a slideshow to present to stakeholders. What else might they do in this step?
  • Collect data.
  • Communicate findings.
  • Organize the available information
  • Shred paper files.

 

  1. If a cooking supply store wants to attract more customers, where can they advertise to better reach their target audience? Select all that apply.
  • On TV during the season finale of The Best Chef in the Universe
  • At a bus stop near a local culinary school
  • On a podcast for foodies
  • In a magazine all about advertising

 

  1. Making predictions is one of the six data analytics problem types. How does data factor into such problem types?
  • The data informs the predictions.
  • The data confirms the decisions.
  • The data are the predictions.
  • The predictions validate the data.

 

  1. Which of the following examples are closed-ended questions? Select all that apply.
  • How tall are you?
  • What did you think about the article that I sent you?
  • What is your opinion of the new movie?
  • Have you taken this class before?

 

  1. What is the defining characteristic of measurable questions?
  • They are questions that have numbers in them.
  • Their answers are numbers that can be interpreted qualitatively.
  • They are questions that use numbers as categories.
  • Their answers are numbers that can be interpreted mathematically.

 

  1. Fill in the blank: “How many people filled out the survey?” is an example of a question that is _____ in the context of data analysis.
  • categorical
  • symbolic
  • measureable
  • qualitative

 

Week 2 – Data-driven decisions

 

An analyst is working with data from two school programs. They discover that the data is measured differently across programs and this may impact how they can work with the data. What does this example describe?

  • Data-inspired decision-making
    • Data-driven decision-making
  • The limitations of working with data
  • Data that cannot be analyzed

 

A retail store runs a special sale with the goal of increasing sales over the holiday season. They use the increase in sales over the same month last year as a starting point. What type of goal is this an example of?

  • Metric goal
  • Theoretical goal
  • Finite goal
  • Conceptual goal

 

A data analyst assesses how well their company’s marketing campaign is performing. They apply a formula that compares the cost of the campaign and its net profit. What does this formula measure?

  • The return on investment
  • Total revenue
  • The average cost
  • Total cost

 

  1. Which of the following statements describes an algorithm?
  • A process or set of rules to be followed for a specific task
  • A method for recognizing the current problem or situation and identifying the options
  • A tool that enables data analysts to spot something unusual
  • A technique for focusing on a single topic or a few closely related ideas

 

  1. Fill in the blank: If a data analyst is measuring qualities and characteristics, they are considering _____ data.
  • quantitative
  • unbiased
  • cleaned
  • qualitative

 

  1. In data analytics, reports use live, incoming data from multiple datasets; dashboards use static collections of data.
  • True
  • False

 

  1. A pivot table is a data-summarization tool used in data processing. Which of the following tasks can pivot tables perform? Select all that apply.
  • Group data
  • Clean data
  • Calculate totals from data
  • Reorganize data

 

  1. A metric is a single, quantifiable type of data that can be used for what task?
  • Setting and evaluating goals
  • Defining a problem type
  • Cleaning data
  • Sorting and filtering data

 

  1. Which of the following options describes a metric goal? Select all that apply.
  • Evaluated using metrics
  • Indefinite
  • Measurable
  • Based on theory

 

  1. Fill in the blank: Return on investment compares the _____ of an investment to the net profit gained from that investment.
  • success
  • purpose
  • cost
  • timing

 

  1. Fill in the blank: A data analyst is using data to address a large-scale problem. This type of analysis would most likely require _____. Select all that apply.
  • small data
  • data that reflects change over time
  • data represented by a limited number of metrics
  • big data

 

 

Shuffle Q/A

  1. Fill in the blank: In data analytics, qualitative data _____. Select all that apply.
  • is always time bound
  • measures qualities and characteristics
  • is subjective
  • measures numerical facts

 

  1. Fill in the blank: A _____ is a data-summarization tool used to sort, reorganize, group, count, total, or average data.
  • report
  • dashboard
  • function
  • pivot table

 

  1. Fill in the blank: A _____ goal is measurable and evaluated using single, quantifiable data.
  • metric
  • finite
  • conceptual
  • benchmark

 

  1. Describe the main differences between big and small data.
  • Small data is typically stored and organized in databases. Big data is typically stored and organized in spreadsheets.
  • Small data is less useful to data analysts. Big data is more useful to data analysts.
  • Small data is specific and concerns a short time period. Big data is less specific and concerns a longer time period.
  • Small data has been cleaned and sorted. Big data has not yet been cleaned or sorted.

 

  1. In data analytics, a pattern is defined as a process or set of rules to be followed for a specific task.
  • True
  • False

 

  1. In data analytics, quantitative data measures qualities and characteristics.
  • True
  • False

 

  1. In data analytics, reports use data that doesn’t change once it’s been recorded. Which of the following terms describes this type of data?
  • Comprehensive
  • Real-time
  • Monitored
  • Static

 

  1. Which data-summarization tool do data analysts use to sort, reorganize, group, count, total, or average data?
  • A function
  • A pivot table
  • A dashboard
  • A report

 

  1. A metric is a specific type of data that companies use to identify a problem domain.
  • True
  • False

 

  1. Fill in the blank: A metric goal is a _____ goal set by a company that is evaluated using metrics.
  • finite
  • theoretical
  • conceptual
  • measurable

 

  1. A data analyst is using data from a short time period to solve a problem related to someone’s day-to-day decisions. They are most likely working with small data.
  • True
  • False

 

  1. If a data analyst compares the cost of an investment to the net profit of that investment over a period of time, they’re analyzing the investment scope.
  • True
  • False

 

  1. What is an example of using a metric? Select all that apply.
  • Using column headers to sort and filter data
  • Using annual profit targets to set and evaluate goals
  • Using key performance indicators, such as click-through rates, to measure revenue
  • Using a pie chart to visualize data

 

  1. Fill in the blank: In data analytics, a process or set of rules to be followed for a specific task is _____.
  • a pattern
  • a domain
  • an algorithm
  • a value

 

  1. Fill in the blank: Return on investment compares the cost of an investment to the _____ of that investment.
  • purpose
  • timing
  • net profit
  • future success

 

Week 3 – More spreadsheet basics

 

What calculations can you carry out within a spreadsheet? Select all that apply.

  • Minimum
  • Maximum
  • Copying
  • Average

 

What are some of the ways that data analysts can gather data? Select all that apply.

  • Use data received from a colleague
  • Use data they collect themselves
  • Use data from open source locations
  • Use restricted data from the government

 

You sum the entries in cells F3 through F200 in your spreadsheet. What is the correct function for this?

  • =SUM(F3+F200)
    • =SUM(F3;F200)
    • =SUM(F3,F200)
  • =SUM(F3:F200)

 

What are some of the causes of bias in data analytics? Select all that apply.

  • Cultural differences
  • Social norms
  • Multiple perspectives
  • Serving an agenda

 

  1. Fill in the blank: In spreadsheets, data analysts begin _____ with an equal sign (=).
  • cells
  • numbers
  • formulas
  • charts

 

  1. Fill in the blank: The labels that describe the type of data contained in each column of a spreadsheet are called _____.
  • assignments
  • attributes
  • allowances
  • aspects

 

  1. Which of the following tasks might be performed using spreadsheets?
  • Maintain information about accounts
  • Write a sales pitch
  • Develop communication skills
  • Land a new client

 

  1. Formulas are created by the user, whereas functions are preset commands in spreadsheets.
  • True
  • False

 

  1. In the function =MAX(B5:B15), what does B5:B15 represent?
  • Observation
  • Column
  • Attribute
  • Range

 

  1. What is the correct spreadsheet formula for multiplying cell H2 times cell H5?
  • =H2/H5
  • =H2^H5
  • =H2*H5
  • =H2xH5

 

  1. To avoid bias when collecting data, a data analyst should keep what in mind?
  • Context
  • Opinion
  • Stakeholders
  • Graphs

 

  1. A data analyst might use descriptive column headers in order to achieve what goal?
  • Add context to their data
  • Protect the spreadsheet
  • Alphabetize the spreadsheet data
  • Filter the data

 

Shuffle Q/A

  1. To determine an organization’s annual budget, a data analyst might use a slideshow.
  • True
  • False

 

  1. Which of the following are ways that data analysts can add context to their data? Select all that apply.
  • Use descriptive column headers
  • Consider where the data came from
  • Create reports for stakeholders
  • Ask questions about the data

 

  1. In spreadsheets, formulas and functions end with an equal sign (=).
  • True
  • False

 

  1. A data analyst could use spreadsheets to achieve which of the following tasks?
  • Motivate employees
  • Write reports
  • Build code for a new app
  • Predict next quarter’s sales

 

  1. In the function =MAX(G3:G13), what does G3:G13 represent?
  • an attribute
  • an observation
  • The range
  • a table

 

  1. What is the correct spreadsheet formula for multiplying cell D5 times cell D7?
  • =D5xD7
  • =D5^D7
  • =D5*D7
  • =D5/D7

 

  1. Fill in the blank: A data analyst considers which organization created, collected, or funded a dataset in order to understand its _____.
  • structure
  • detail
  • length
  • context

 

  1. Which of the following statements accurately describe formulas and functions? Select all that apply.
  • Formulas are instructions that perform specific calculations.
  • Formulas may only be used once per spreadsheet column.
  • Functions are preset commands that perform calculations.
  • Formulas and functions assist data analysts in calculations, both simple and complex.

 

  1. In the function =MAX(B5:B15), what does B5:B15 represent?
  • Attribute
  • Column
  • Observation
  • Range

 

  1. What is the correct spreadsheet formula for multiplying cell H2 times cell H5?
  • =H2*H5
  • =H2/H5
  • =H2xH5
  • =H2^H5

 

  1. Both formulas and functions in spreadsheets begin with what symbol?
  • Equal sign (=)
  • Colon (:)
  • Hyphen (-)
  • Bracket ([)

 

  1. Fill in the blank: By negatively influencing data collection, ____ can have a detrimental effect on analysis.
  • objectivity
  • bias
  • partiality
  • filtering

 

  1. Attributes are used in spreadsheets for what purpose?
  • Analyze the data in a row
  • Insert data into each column
  • Add a new column
  • Label the data in each column

 

  1. To determine an organization’s annual budget, a data analyst might use a slideshow.
  • True
  • False

 

  1. Which of the following statements describes a key difference between formulas and functions?
  • Formulas contain words and numbers, and functions contain numbers only.
  • Formulas span two or more cells, and functions exist in only one cell.
  • Formulas are used in graphs, and functions are not.
  • Formulas are written by the user, and functions are already defined.

 

  1. What do data analysts use to label the type of data contained in each column in a spreadsheet?
  • Tables
  • Menus
  • Attributes
  • Headings

 

  1. In the function =MAX(A1:A12), what does A1:A12 represent?
  • The range
  • The operator
  • The maximum
  • The formula

 

  1. Fill in the blank: Putting data into context helps data analysts eliminate _____.
  • labels
  • intolerance
  • bias
  • fairness

 

Week 4 – Always remember the stakeholder

 

Fill in the blank: Your data analytics team is working on a project for the marketing department. The person most likely to be the _____ stakeholder is the vice president of marketing.

  • primary
  • necessary
  • secondary
  • project

 

To communicate clearly with stakeholders and team members, there are four key questions data analysts ask themselves. One of the questions is: What does my audience already know? Identify the remaining three questions. Select all that apply.

  • What does my audience need to know?
  • How can I communicate effectively to my audience?
  • Why are stakeholders and team members important?
  • Who is my audience?

 

You accept a new project from a high level stakeholder. After beginning the project, you find that you aren’t sure what you are supposed to do. How do you handle this?

  • Determine the objectives that make the most sense and work towards those.
  • Set up a meeting with the stakeholder to discuss the specific objectives they wanted.
  • Ask a member of your team what was done on the last project and do the same.
  • Perform the standard analysis and present its insights.

 

A data analyst collects a large amount of data for their project to ensure that the data represents a diverse set of perspectives. What element of data collection does this describe?

  • Sample size
  • Statistical significance
  • Visualization
  • Data cleaning

 

When leading a meeting, it is important to respect your team members’ time. What are some ways of doing this? Select all that apply.

  • Pay attention to what others are saying
  • Arrive to the meeting on time
  • Discuss work that does not impact the attendees.
  • Be prepared to talk about your work

 

What are some of the “don’ts” when attending a meeting?

  • Don't dominate the conversation.
  • Don't show up unprepared.
  • Don’t arrive late.
  • Don’t arrive early.

 

Your manager assigns you a project task, and you don’t understand the point of the project. What questions can you ask them to determine the objective? Select all that apply.

  • What is their end goal?
  • What do you have to do for this task?
    • What is the story they want to tell?
  • What is the big picture?

 

  1. A data analyst starts a new project for the operations team at their company. They take a few hours at the beginning of the project to identify their stakeholders. The secondary stakeholders are most likely which of the following people? Select all that apply.
  • The data analyst
  • The project manager
  • The president of the company
  • The vice president of operations

 

  1. A data analyst is researching the buying behavior of people who shop at a company’s retail store and those who might shop there in the future. During the analysis, it will be important to stay in communication with the people who most often interact with these shoppers. They are members of the executive team.
  • True
  • False

 

  1. There are four key questions data analysts ask themselves: Who is my audience? What do they already know? What do they need to know? And how can I communicate effectively with them? These questions enable data analysts to achieve what goal?
  • Understand who is managing the data
  • Communicate clearly with stakeholders and team members
  • Identify primary and secondary stakeholders
  • Complete data analysis projects on time

 

  1. Data analysts pay attention to sample size in order to achieve what goals? Select all that apply.
  • To fully understand the scope of the analytics project
  • To avoid a small sample size leading to inaccurate judgements
  • To make sure the data represents a diverse set of perspectives
  • To make sure a few unusual responses don’t skew results

 

  1. A data analyst receives an email from the vice president of marketing. The vice president is upset because the report they want from the analyst is late. Select the best course of action.
  • The analyst should call the vice president and ask them how important it really is to their marketing efforts.
  • The analyst should send the report immediately, even if it’s not completely finished. This will make the vice president happy.
  • The analyst should respond saying they understand the vice president’s concerns, provide a status update, and let the vice president know when to expect the completed report.
  • The analyst should apologize for the delay and inform the vice president that the marketing managers caused the delay.

 

  1. Arriving at meetings prepared is an important part of creating a professional work environment. This involves which of the following actions? Select all that apply.
  • Bringing materials to take notes with
  • Considering what questions you may be asked so you’re prepared to answer
  • Reading the meeting agenda ahead of time
  • Bringing a laptop to keep an eye on emails

 

  1. A data analyst joins an online meeting on time. After reviewing the agenda, they see that their project comes at the very end. They’re extremely busy and can use this time to stay on top of their current projects. How should they proceed?
  • Mute themselves and turn off the camera, then continue working on other tasks until their project is mentioned.
  • Tell the participants that they’re having technical trouble, then leave the meeting to continue working on other tasks.
  • Politely let the presenter know they’re going to leave the meeting and rejoin toward the end.
  • Stay focused and attentive during the entire meeting. Even though some items on the agenda don’t affect their projects, they could still learn something or have something to contribute.

 

  1. Your data analytics team has been working on a project for a few weeks. You’re almost done, when your supervisor suddenly changes the business task. Everyone has to start all over again. You announce to the team that you’re going to say something to the supervisor about how unreasonable this is. What’s the best next step?
  • Insist that the entire data analytics team complain to your supervisor.
  • Go see your supervisor face-to-face and tell them why you’re so upset.
  • Write a polite, but strongly worded email to your supervisor.
  • Take a few minutes to calm down, then ask your colleagues to share their perspectives so you can work together to determine the best next step.

 

Shuffle Q/A

  1. A data analyst is researching the buying behavior of people who shop at a company’s retail store and those who might shop there in the future. During the analysis, it will be important to stay in communication with the team that most often interacts with these shoppers. What is the name of this team?
  • Data science team
  • Project management team
  • Executive team
  • Customer-facing team

 

  1. You receive an angry email from a colleague on the marketing team. The marketing colleague believes you have taken credit for their work. You do not believe this is true. Select the best course of action.
  • Delete the email. It’s best not to create any additional conflict.
  • Reply to the email, asking if they can schedule a time to talk about this in person in order to allow both of you to share your perspectives.
  • Walk over to the marketing colleague’s cubicle, and tell them you strongly disagree.
  • Forward the email to the marketing director with an equally angry note.

 

  1. A data analyst has been invited to a meeting. They review the agenda and notice that their data analysis project is one of the topics that will be discussed. How can they prepare for an effective meeting? Select all that apply.
  • Bring materials for taking notes.
  • Plan to arrive on time.
  • Think about what project updates they should share.
  • Create and share a revised agenda that includes many more details about their project.

 

  1. Which of the following steps are key to leading a professional online meeting? Select all that apply.
  • Maintaining control of the meeting by keeping everyone else on mute.
  • Sitting in a quiet area that’s free of distractions
  • Making sure your technology is working properly before starting the meeting
  • Keeping an eye on your inbox during the meeting in case of an important email

 

  1. A team member has asked you to take on a task, and you don’t understand the point of the project. It seems like it will be a waste of your time. The best course of action would be to politely explain your concerns and decline the project.
  • True
  • False

 

  1. Fill in the blank: A data analytics team is working on a project to measure the success of a company’s new financial strategy. The vice president of finance is most likely to be the _____.
  • project manager
  • analyst
  • primary stakeholder
  • secondary stakeholder

 

  1. At an online marketplace, the _____ includes anyone in an organization who interacts with current or potential shoppers.
  • executive team
  • data science team
  • project management team
  • customer-facing team

 

  1. There are four key questions data analysts ask themselves: Who is my audience? What do they already know? What do they need to know? And how can I communicate effectively with them? These questions enable data analysts to identify the person in charge of managing the data.
  • True
  • False

 

  1. A data analyst has been invited to a meeting. They review the agenda and notice that their data analysis project is one of the topics that will be discussed. They plan to arrive on time and have a pen and paper to take notes. But they do not spend time considering project updates they could share or questions they may be asked. This is appropriate because they’re not the one running the meeting.
  • True
  • False

 

  1. A data analytics team is working on a project to measure the success of a company’s new financial strategy. Select the person most likely to be the primary stakeholder for this project.
  • The project manager
  • The data analyst
  • The vice president of finance
  • The director of analytics

 

  1. To communicate clearly with stakeholders and team members, there are four key questions data analysts ask themselves. One of them is: What does my audience need to know? Identify the remaining three questions. Select all that apply.
  • Why are stakeholders and team members important?
  • Who is my audience?
  • How can I communicate effectively to my audience?
  • What does my audience already know?

 

  1. Conflict is a natural part of working on a team. What are some ways to help shift a situation from problematic to productive? Select all that apply.
  • Take a moment to check your emotions before engaging in an argument.
  • Ask for a conversation to help you better understand the big picture.
  • Reframe the question by asking, “How can I help?”
  • Identify the person who caused the issue so they can take responsibility.

 

  1. Data analysts focus on statistical significance to make sure they have enough data so that a few unusual responses don’t skew results
  • True
  • False

 

  1. A data analyst feels overworked. They often stay late to finish work, and have started missing deadlines. Their supervisor emails them another project to complete, and this causes the analyst even more stress. How should they handle this situation?
  • Accept the new project right away and hope to not miss another deadline.
  • Wait a few minutes to think it over, then respond with a meeting request to discuss this project and the general workload.
  • Walk into the supervisor’s office and tell them to give the project to someone else.
  • Respond immediately, letting the supervisor know the expectations at this company are unreasonable.

 

  1. When participating in an online meeting, it’s okay to keep your inbox open in another browser window. Participants won’t be distracted because they can’t see it, and you might receive a very important message.
  • True
  • False

 

Course challenge

 

Scenario 1, questions 1-5

You’ve just started a job as a data analyst at a small software company that provides data analytics and business intelligence solutions. Your supervisor asks you to kick off a project with a new client, Athena’s Story, a feminist bookstore. They have four existing locations, and the fifth shop has just opened in your community.

Athena’s Story wants to produce a campaign to generate excitement for an upcoming celebration and introduce the bookstore to the community. They share some data with your team to help make the event as successful as possible.

Your task is to review the assignment and the available data, then present your approach to your supervisor. Click the link below to access the email from your supervisor:

Course 2 Scenario 1 Email from Supervisor.pdf

PDF File

Then, review the email, and the Customer Survey and Historical Sales datasets.

To use the templates for the datasets, click the links below and select “Use Template.”

Links to templates: Customer Survey and Historical Sales

OR

If you don't have a Google account, you can download the CSV files directly from the attachments below.

CustomerSurvey - CustomerSurvey

CSV File

HistoricalSales - HistoricalSales

CSV File

After reading the email, you notice that the acronym WHM appears in multiple places. You look it up online, and the most common result is web host manager. That doesn’t seem right to you, as it doesn’t fit the context of a feminist bookstore. Still, you should assume it’s correct and continue with the project.

  • True
  • False

Scenario 1 continued

Now that you know WHM stands for Women’s History Month, you continue reviewing the datasets. You notice that the Customer Survey dataset contains both qualitative and quantitative data.

To use the template for the dataset, click the link below and select “Use Template.”

Link to template: Customer Survey

OR

If you don't have a Google account, you can download the CSV file directly from the attachment below.

CustomerSurvey - CustomerSurvey

CSV File

The qualitative data includes information from which columns? Select all that apply.

  • Column E (Survey Q5: What do you like most about Athena's Story?)
  • Column B (Survey Q2: If answered "Yes" to Q1, how do you plan to celebrate?)
  • Column D (Survey Q4: If answered "Yes" to Q3, how many books do you typically purchase during March?)
  • Column F (Survey Q6: What types of books would you like to see more of at Athena's Story?)

 

Scenario 1 continued

Next, you review the customer feedback in column F of the Customer Survey dataset.

To use the template for the dataset, click the link below and select “Use Template.”

Link to template: Customer Survey

OR

If you don't have a Google account, you can download the CSV file directly from the attachment below.

CustomerSurvey - CustomerSurvey

CSV File

The attribute of column F is, “Survey Q6: What types of books would you like to see more of at Athena's Story?” In order to verify that children’s literature and feminist zines are among the most popular genres, you create a visualization. This will help you clearly identify which genres are most likely to sell well during the Women’s History Month campaign.

Your visualization looks like this:

Pie chart categories: -Feminist science fiction 4.8% -Books about women 2.4% -Women's journals 2.4% -Feminist literary criticism 2.4% -Children's literature 15.5% -Women's history books 2.4% -Biographies of inspiration 20.2% -Feminist fiction 26.2% -Feminist zines 14.3% -Feminist poetry 4.6% -Feminist novels 3.6%

Pie chart categories: Feminist science fiction 4.8% Books about women 2.4% Women's journals 2.4% Feminist literary criticism 2.4% Children's literature 15.5% Women's history books 2.4% Biographies of inspiration 20.2% Feminist fiction 26.2% Feminist zines 14.3% Feminist poetry 4.6% Feminist novels 3.6%

Fill in the blank: The visualization you create demonstrates the percentages of each book genre that make up the total number of survey responses. It’s called a _____ chart.

  • bubble
  • pie
  • doughnut
  • area

 

Now that you’ve confirmed that children’s literature and feminist zines are among the most requested book genres, you review the Historical Sales dataset.

To use the template for the dataset, click the link below and select “Use Template.”

Link to template: Historical Sales

If you don't have a Google account, you can download the CSV file directly from the attachment below.

HistoricalSales - HistoricalSales

CSV File

You’re pleased to see that the dataset contains data that’s specific to children’s literature and feminist zines. This will provide you with the information you need to make data-inspired decisions. In addition, the children’s literature and feminist zines metrics will help you organize and analyze the data about each genre in order to determine if they’re likely to be profitable.

Next, you calculate the total sales over 52 weeks for feminist zines. You type =CALCULATE(E2-E53) but get an error. What is the correct syntax?

  • =MAX(E2:E53)
    • =COUNT(E2:E53)
  • =SUM(E2:E53)
  • =CALC(E2:E53)

 

Scenario 1 continued

After familiarizing yourself with the project and available data, you present your approach to your supervisor. You provide a scope of work, which includes important details, a schedule, and information on how you plan to prepare and validate the data. You also share some of your initial results and the pie chart you created.

In addition, you identify the problem type, or domain, for the data analysis project. You decide that the historical sales data can be used to provide insights into the types of books that will sell best during Women’s History Month this coming year. This will also enable you to determine if Athena’s Story should begin selling more children’s literature and feminist zines.

Using historical data to make informed decisions about how things may be in the future is an example of spotting something unusual.

  • True
  • False

 

Scenario 2, questions 6-10

You’ve completed this program and are now interviewing for your first junior data analyst position. You’re hoping to be hired by an event planning company, Patel Events Plus. Access the job description below:

Junior Data Analyst Job Description.pdf

PDF File

So far, you’ve successfully completed the first round of interviews with the human resources manager and director of data and strategy. Now, the vice president of data and strategy wants to learn more about your approach to managing projects and clients. Access the email you receive from the human resources director below:

Human Resources Director Email.pdf

PDF File

You arrive Thursday at 1:45 PM for your 2 PM interview. Soon, you’re taken into the office of Mila Aronowicz, vice president of data and strategy. After welcoming you, she begins the behavioral interview.

First, she hands you a copy of Patel Events Plus’s organizational chart. Access the chart below:

Patel Event Plus Org Chart.pdf

PDF File

As you’ve learned in this course, stakeholders are people who invest time, interest, and resources into the projects you’ll be working on as a data analyst. Let’s say you’re working on a project involving data and strategy.

Based on what you find in the organizational chart, who should be considered the primary stakeholder for projects involving data and strategy?

  • Director
    • Project manager
    • Chief executive officer
  • Vice president

 

Scenario 2 continued

Next, the vice president wants to understand your knowledge about asking effective questions. Consider and respond to the following question. Select all that apply.

Let’s say we just completed a big event for a client and wanted to find out if they were satisfied with their experience. Provide some examples of measurable questions that you could include in the customer feedback survey. Select all that apply.

  • Would you recommend Patel Events Plus to a colleague or friend? Yes or no?
  • Why did you enjoy the event planned by Patel Events Plus?
  • On a scale from 1 to 5, with 1 being not at all likely and 5 being very likely, how likely are you to recommend Patel Events Plus?
  • How would you describe your event experience?

 

Scenario 2 continued

Now, the vice president presents a situation having to do with resolving challenges and meeting stakeholder expectations. Consider and respond to the following question.

You’re working on a rush project, and you discover your dataset is not clean. Even though it has numerous nulls, redundant data, and other issues, the primary stakeholder insists that you move ahead and use it anyway. The project timeline is so tight that there simply isn’t enough time for cleaning. How would you handle that situation?

  • Contact the stakeholder’s boss to let them know about the issue and ask for help managing the stakeholder’s expectations.
    • The stakeholder is in charge. It's best to do as they say and use the unclean dataset.
    • Clean the data as quickly as you can. It’s not perfect, but it’s better than it was before, and this way you can meet the deadline.
  • Communicate the situation to your supervisor and ask for advice on how to handle the situation with the stakeholder.

 

Scenario 2 continued

Your next interview question deals with sharing information with stakeholders. Consider and respond to the following question. Select all that apply.

Let’s say you’ve designed a dashboard to give stakeholders easy, automatic access to data about an upcoming event. Describe the benefits of using a dashboard. Select all that apply.

  • Dashboards offer live monitoring of incoming data.
  • Dashboards enable stakeholders to interact with the data.
  • Dashboards are easy to design and understand.
  • Dashboards present pre-cleaned, historical data.

 

Scenario 2 continued

Your final behavioral interview question involves using metrics to answer business questions. Your interviewer hands you a copy of a Patel Events dataset.

To use the template for this dataset, click the link below and select “Use Template.”

Link to template: Patel Events Data

OR

If you don't have a Google account, you can download the CSV file directly from the attachment below.

Patel Events Plus dataset

CSV File

Then, she asks: Recently, Patel Events Plus purchased a new venue for our events. If we asked you to calculate the return on investment of this purchase, the metrics to consider would be the cost of the investment and what else?

  • Net profit in 2019
  • Average event revenues
  • 2019 events held at new venue
  • Purchase date

 

Scenario 1, questions 1-5

You’ve just started a job as a data analyst at a small software company that provides data analytics and business intelligence solutions. Your supervisor asks you to kick off a project with a new client, Athena’s Story, a feminist bookstore. They have four existing locations, and the fifth shop has just opened in your community.

Athena’s Story wants to produce a campaign to generate excitement for an upcoming celebration and introduce the bookstore to the community. They share some data with your team to help make the event as successful as possible.

Your task is to review the assignment and the available data, then present your approach to your supervisor. Click the link below to access the email from your supervisor:

Course 2 Scenario 1 Email from Supervisor.pdf

PDF File

Then, review the email, and the Customer Survey and Historical Sales datasets.

To use the templates for the datasets, click the links below and select “Use Template.”

Links to templates: Customer Survey and Historical Sales

OR

If you don't have a Google account, you can download the CSV files directly from the attachments below.

CustomerSurvey - CustomerSurvey

CSV File

HistoricalSales - HistoricalSales

CSV File

After reading the email, you notice that the acronym WHM appears in multiple places. You look it up online, and the most common result is web host manager. That doesn’t seem right to you, as it doesn’t fit the context of a feminist bookstore. You email your supervisor to ask. When writing your email, what do you do to ensure it sounds professional? Select all that apply.

  • Respect your supervisor’s time by writing an email that’s short and to the point.
  • Use a polite greeting and closing.
  • Read your email aloud before sending to catch any typos or grammatical errors and to ensure the communication is clear.
  • Write a clear subject line that gets a fast response so you can keep working: “WHM? NEED TO KNOW WHAT THAT IS RIGHT AWAY.”

 

Scenario 1 continued

Now that you know WHM stands for Women’s History Month, you continue reviewing the datasets. You notice that the Customer Survey dataset contains both qualitative and quantitative data.

To use the template for the dataset, click the link below and select “Use Template.”

Link to template: Customer Survey

OR

If you don't have a Google account, you can download the CSV file directly from the attachment below.

CustomerSurvey - CustomerSurvey

CSV File

The quantitative data includes information from which columns? Select all that apply.

  • Column D (Survey Q4: If answered "Yes" to Q3, how many books do you typically purchase during March?)
  • Column C (Survey Q3: Do you purchase feminist books in honor of WHM, either for yourself or as a gift for someone else?)
  • Column E (Survey Q5: What do you like most about Athena's Story?)
  • Column A (Survey Q1: Do you plan to celebrate WHM?)

 

Scenario 2, questions 6-10

You’ve completed this program and are now interviewing for your first junior data analyst position. You’re hoping to be hired by an event planning company, Patel Events Plus. Access the job description below:

Junior Data Analyst Job Description.pdf

PDF File

So far, you’ve successfully completed the first round of interviews with the human resources manager and director of data and strategy. Now, the vice president of data and strategy wants to learn more about your approach to managing projects and clients. Access the email you receive from the human resources director below:

Human Resources Director Email.pdf

PDF File

You arrive Thursday at 1:45 PM for your 2 PM interview. Soon, you’re taken into the office of Mila Aronowicz, vice president of data and strategy. After welcoming you, she begins the behavioral interview.

First, she hands you a copy of Patel Events Plus’s organizational chart. Access the chart below: