Ask Questions - Google Data Analytics Course 2 Quiz Answers (2023)

Coursera Google Data Analytics Professional Certificate Course 2 - Ask questions to make data-driven decisionsQuiz answers to all weekly questions (weeks 1-4):

• Week 1: Effective Questions
• Week 2: Data-driven decisions
• Week 3: More spreadsheet basics
• Week 4: Always think of the stakeholder
• natural challenge

You might also be interested inGoogle Kurs 1 Data Analysis Professional Certificate: Grundlagen – Cliffs Notes.

Week 1: Ask effective questions

This course starts with troubleshooting and some of the most common types of business problems that data analysts help solve.

To do the job of a data analyst, you must ask questions and solve problems. In this part of the course, you'll look at some common analytics problems and how analysts solve them. You will also learn effective questioning techniques that can help you with your analysis.

learning goals

• Explain the characteristics of effective questions related to the SMART framework
• Discuss the most common types of issues a data analyst addresses
• Explain how each step of the troubleshooting roadmap contributes to high-level analysis scenarios
• Explain the data analysis process, referring specifically to the Ask, Prepare, Process, Analyze, Share, and Act phases
• Describe key ideas associated with structured thinking, including problem domain, scope of work, and context.

1.1. Effective problem solving and questioning.

Problem solving starts with effective questions.

From Problem to Action: The six phases of data analysis are Ask, Prepare, Process, Analyze, Share, and Act.

<SoldierQuestionsIn Step 1, we define the problem we are solving and ensure we fully understand stakeholder expectations.>

1.2. business data

1.2.1. Data in action (the data analysis process)

A brief data analysis case study shows how the six phases of data analysis can be applied to effectively solve real-world problems: Anywhere Gaming Repair is a service provider for small businesses looking to you for system repair or accessories damaged video games. “The owner wanted to expand his business. I knew advertising was a proven way to get more customers, but I didn't know where to start," especially in terms of a) appropriate media (i.e. who is the target audience and what media do they use?) and 2) the advertising budget (how much different advertising methods will cost) The business owner asks a data analyst, Maria, for a recommendation.

Step 1: Maria starts withdefine the problemthat had to be resolved by working with stakeholders and understanding their needs.

Anywhere Gaming Repair wants to know how to get new customers. So the problem is to determine the best advertising method for the target audience. The collected data will answer this problem.

Step 2: The next step was theprepareIn this phase, Maria collected data for the next analysis process.

First, he needed to better understand the company's target audience; There are people with video game systems. Next, Maria collected data on different advertising methods... to determine which was most popular with the company's target audience.

This is where a data analyst tries to understand their audience. < They ask questions like "How can learning more about my target audience help me figure out how to solve this problem?" and "What research should I do about my target audience?">

Step 3: He then proceeded toprocessStage. Here, Maria cleaned up the data to remove any errors, inaccuracies, or inconsistencies "that could interfere with the result... By cleaning up the data, you transform it into a more useful format, create more complete information, and remove discrepancies."

This is where an analyst asks questions like "What data flaws could be interfering with my analysis?" or "How can I clear my data so the information I have is consistent?">

Step 4: Then the time has cometo analyze🇧🇷 At this stage, Maria wanted to find out two things.

First, who is most likely to own a video game system? (People between 18 and 34 years old). Second, where are these people most likely to see an ad? (TV commercials and podcasts are very popular with the target audience.)

Step 5: Now it's Maria's turnPull apartyour recommendation so the company can make a data-driven decision. “She summarized her findings with clear and compelling visualizations of the analysis. This helped stakeholders understand the solution to the original problem.”

Step 6: Finally, Anywhere Gaming Repair has been performedaction, they worked with a local podcast production agency to create a 30-second commercial about their services. The ad ran on the podcast for a month and it worked. They saw an increase in customers within the first week. By the end of the fourth week, they had 85 new customers.

1.2.2.From problem to action: the six phases of data analysis

1.2.3. Here's how the data analysis process works (example/short case study): "One of the issues we're tackling here at Google is our Noogler onboarding program, which we use to onboard new hires."

<One of the things we did wasask the questionSo how do we know nooglers will be onboarded faster through our new onboarding program than through the old onboarding program we used to teach them? We worked closely with content providers to understand exactly what it means to onboard someone faster.

<When we all asked questions...weListthe data understanding who was the new hire population that we studied... who was our sample set, who was our control group, who was our experimental group, where our data sources were and making sure it was a set , in a format that was clean and digestible for us to write the right scripts for it.

<So the next step for us wasprocessthe data to make sure it's in a format that we can actually parse it in SQL to make sure it's in the right format, columns and tables for us.

<Ato analyzeWith the data, we wrote SQL and R scripts to correlate the data with the control group or the experimental group and interpret the data to understand if there were changes in the behavioral indicators that we saw.

<After we have analyzed all the data, we want you toMessageso that our stakeholders could understand... We create reports, dashboards and presentations and share this information.

<After we finished all our reports, we saw really positive results and we were able toGraphicon it, continuing our project-based learning integration program.>

1.3. solve problems with data

Data analysts work with six basic types of problems:

• Make predictions (for example, a company that wants to know which advertising method is best for attracting new customers, for example, Anywhere Gaming Repair);
• Categorize things (for example, a data analyst identifying and ranking keywords from customer reviews to improve customer satisfaction);
• Discovering something unusual (for example, a company that sells smartwatches that help people monitor their health, for example, resting heart rate suddenly increases to 120 beats per minute);
• Identify themes (Insights are grouped into broader themes, for example, in UX improvement projects, analysts can be asked to identify themes to prioritize the right product features to improve);
• Discovery of connections (for example, an external logistics company working with another company to deliver shipments to customers on time);
• Find patterns (in historical data, for example, minimizing downtime caused by machine failures).

1.4. Create effective questions

We'll learn how to create effective questions that lead to important information that you can use to resolve all types of SMART Framework issues, and how to ensure your questions are fair and objective.

To start solving a problem, data analysts first ask effective questions. Effective questions can be created using the SMART methodology.

That is, they are specific, measurable, action-oriented, relevant and time-bound.

SpecificQuestions are simple, meaningful, and focus on a single topic or a few closely related ideas (for example, what percentage of children get the recommended 60 minutes of physical activity at least five days a week? What are the top five resources you want in a car package?)

MeasurableQuestions can be quantified and scored (for example, how many times was our video shared on social channels in the first week it was posted? On a scale of 1 to 10, 10 being most important, how important is it that your car has traction on four wheels?)

action orientedQuestions inspire change (e.g., what design features make our packaging more recyclable?)

ImportantThe questions are important, important and have relevance to the problem you are trying to solve (e.g. what are the top five features you would like to see in a car package?)

limited in timeQuestions specify the time period to be studied (eg, 1983 to 2004; has four-wheel drive become more or less popular in the last three years?)

questions” mustOpen🇧🇷 This is the best way to get answers that will help you accurately rank or downgrade possible solutions to your specific problem.”

questions must beMesse🇧🇷 Questions do not create or reinforce bias. “Equity also means asking questions that make sense for everyone. The questions are clear and simple so that anyone can easily understand." Unfair questions include leading questions (this product is great, isn't it?)

Answers to week 1 quiz questions

diagnostic questionnaire

question 1

Categorizing things is one of the six types of problems that data analysts solve. Which of the following actions could involve this type of problem?

• Sort or group items
• Use data to imagine how something might happen in the future
• Notice something out of the ordinary
• Analyze how one action leads to or affects another

Categorizing things involves sorting or grouping items for information.

question 2

Finding patterns is one of six types of problems that data analysts aim to solve. Which of the following issues might be affected by this type of issue?

• Take categorized items and group them into broader subject areas
• Notice something out of the ordinary
• Analyze how one action leads to or affects another
• Identify trends from historical data

Finding patterns involves identifying trends from historical data.

question 3

The SMART methodology outlines questions that encourage change, such as?

• Important
• Specific
• limited in time
• action oriented

Action-oriented questions spur change.

question 4

Fill in the blank: In data analysis, qualitative data_🇧🇷 Select all that apply.

• measures numbers facts
• measures qualities and characteristics
• is specific
• it's subjective

Qualitative data are subjective and measure qualities and characteristics.

question 5

How are dashboards different from reports in data analysis?

• Dashboards contain static data. Reports contain data that is constantly changing.
• Dashboards are only used to share updates with stakeholders on a regular basis. Reports provide stakeholders with continuous access to data.
• Dashboards provide an overview of historical data. Reports provide a more detailed view of live interactive data.
• Dashboards monitor live data received from multiple datasets and organize the information in a central location. Reports are static collections of data.

Dashboards monitor live data received from multiple datasets and organize the information in a central location. Reports are static collections of data.

question 6

How is small data different from big data? Select all that apply.

• Small data focuses on short, well-defined time periods. Big data focuses on changes over a long period of time.
• Small data is usually stored in a database. Big data is usually stored in a table.
• Small data is effective for analyzing day-to-day decisions. Big data is effective for analyzing more fundamental decisions.
• Small data are sets of data that deal with a small number of specific metrics. Big data includes larger and less specific datasets.

Small data includes a small number of specific metrics over a shorter time period. It is effective for analyzing day-to-day decisions. Big data includes larger, less specific datasets and focuses on changes over a long period of time. It is effective for analyzing more substantive decisions.

question 7

Fill in the blank: Some of the most common symbols used in formulas are + (addition), – (subtraction), * (multiplication), and / (division). these are called_.

• references
• operator
• account
• Domains

Operators are symbols used in formulas, including + (addition), – (subtraction), * (multiplication), and / (division).

question 8

In the function =SUM(G1:G35), identify the range.

• G1:G35
• = SOMA
• G35
• =SOMA(G1)

In the function =SUM(G1:G35), the range is G1:G35. A range is a collection of two or more cells.

question 9

To solve a vague and complex problem, a data analyst breaks it down into smaller steps. They use a process that helps them recognize the current problem or situation, organize available information, uncover gaps and opportunities, and identify options. What does this scenario describe?

• Gap analysis
• structured thinking
• Data-based decision making
• analytical thinking

Structured thinking is the process of recognizing the current problem or situation, organizing available information, discovering gaps and opportunities, and identifying options.

question 10

Ask questions like "Does my analysis answer the original question?" and "Are there other perspectives I haven't considered?" allow data analysts to perform what tasks? Select all that apply.

• Identify primary and secondary stakeholders
• Use data to come to a strong conclusion
• Help team members make informed, data-driven decisions
• Consider the best way to share data with others

Data analysts ask thoughtful questions that help them draw solid conclusions, consider how to share data with others, and help team members make effective decisions.

Video: data in action

Marketing analysis is the process of measuring, analyzing, and managing a company's marketing strategy and budget. It is often a matter of identifying the company's target audience.

Which people belong to the target group?

• The people involved in the marketing analytics project.
• The people the company wants to reach
• People most likely to listen to podcasts
• The people on your marketing analytics team

The target audience is the people the company wants to reach.

(Video) week 2 quiz of "Googal data analytics" solution.

Video: Types of common problems

Which of the following might include the Find Pattern problem type?

• Review social media analytics to identify common phrases, categorize them, and group each category into a broader topic
• Use historical data to create a report showing when sales are likely to increase during the upcoming holiday season.
• Review the sales data and find that a random Tuesday in August last year had the highest sales
• Working with a supplier to discover that bad weather is the top reason for late deliveries

The Find Pattern problem type might involve using historical data to generate a report showing when sales are likely to increase during the upcoming holiday season. This type of problem tries to look at trends in historical data to understand what happened in the past and is therefore likely to happen again in the future.

Video: SMART questions

With what component of the SMART methodology do questions that lead to answers that can be quantified and scored align?

• Tangible
• appropriate
• appropriate
• Measurable

Questions that lead to answers that can be quantified and scored are consistent with the measurable component of the SMART methodology.

When considering a research question, a data analyst follows the SMART methodology. They limit their analysis to data from July 2012 to August 2012. Which component of the SMART framework describes this decision?

• reflective
• managed
• At the moment
• limited in time

Limiting the analysis to a certain time period describes issues with time limits. They help narrow down the analysis possibilities and allow data analysts to focus on the most relevant data.

business data

question 1

A data analysis team is working to identify the current issue. They then organize the available information to uncover gaps and opportunities. Finally, they identify the available options. These steps are part of which process?

• with structured thinking
• classify things
• make connections
• SMART methodology application

This describes structured thinking. Structured thinking begins with recognizing the current problem or situation. The information is then organized to reveal gaps and opportunities. Finally, the available options are identified.

question 2

At what stage in the data analysis process would an analyst ask questions such as "What data flaws might be interfering with my analysis?" or "How can I clear my data so the information I have is consistent?"

• Questions
• process
• Prepare
• To analyze

An analyst asks questions like "What data flaws could be interfering with my analysis?" or "How can I clear my data so the information I have is consistent?" during the process step. Data is cleaned to remove possible errors, inaccuracies or inconsistencies.

question 3

A data analyst has entered the analysis step of the data analysis process. Identify questions they might ask at this stage. Select all that apply.

• What story does my data tell me?
• How can I create an attractive presentation for interested parties?
• How does my data help me solve this problem?
• What question am I trying to answer?

The analysis step involves analytical thinking about the data. Data analysts might ask how the data can help them solve the problem and what story the data is trying to tell.

question 4

A data analyst tries to understand his audience. They ask questions like "How can learning more about my audience help me figure out how to solve this problem?" and "What research should I do about my hearing?" What stage of the data analysis process are you at? they data analyst?

• lei
• Pull apart
• Questions
• Prepare

The data analyst is in the preparation stage. At this point, analysts are considering what information to collect and what research to do to resolve the issue.

solve problems with data

question 1

A data analyst identifies keywords from customer reviews and labels them as positive or neutral. This is an example of what kind of problem?

• find patterns
• make predictions
• identify problems
• classify things

A data analyst identifying keywords from customer reviews and labeling them as positive or neutral is an example of categorizing things.

question 2

Which of the following scenarios might involve the Detect Unusual issue type?

• A data analyst at a non-profit arts organization sorts similar data points into groups for further analysis.
• A data analyst working for an agricultural company is investigating why a dataset contains a surprising and rare data point.
• A data analyst at a clothing retailer creates a list of common themes, categorizes them, and groups each category into a broader subject area for further analysis.
• A look at the data helps a landscaping company visualize what will happen in the future

The nature of the problem of spotting something unusual might be for a data analyst to investigate why a dataset contains a surprising and rare data point. To detect something out of the ordinary is to identify and analyze something out of the ordinary.

question 3

A data analyst for an online retailer examines trends in historical sales data. They want to understand what happened in the past and therefore is likely to happen again in the future. This is an example of what kind of problem?

• find patterns
• make predictions
• classify things
• identify problems

An example of looking for patterns is a data analyst looking at trends in historical sales data to understand what has happened in the past and is therefore likely to happen again in the future. Finding patterns is looking at trends in historical data to understand what has happened in the past and is therefore likely to happen again in the future.

Create effective questions

question 1

A data analyst uses SMART methodology to create a question that inspires change. How can you describe this type of question?

• results oriented
• Stimulant
• motivating
• action oriented

In the SMART methodology, the questions that stimulate change are action-oriented.

question 2

A timed SMART question specifies which of the following?

• The subject or matter of analysis
• The desired change that the analysis should produce
• The metrics or key numbers related to the analysis.
• The era, phase, or period of the analysis.

A timed SMART question indicates the era, phase or period of analysis.

question 3

A data analyst working for a midsize retailer writes questions for a customer experience survey. One of the questions is: "Do you prefer to buy online or in the physical store?" Then she rewrites it to say, "Would you rather shop from our online marketplace or your local store?" Describe why this question is more effective.

• The first question is leading, while the second question can have many different answers.
• The first question is closed, while the second question encourages the respondent to elaborate further.
• The first question is vague, while the second provides important context.
• The first question contains jargon that may not make sense to everyone, while the second question is easy to understand.

Vague questions don't provide context. The second question makes it clear that the data analyst wants to know exactly how and where customers prefer to shop.

question 4

A data analyst for a social media company creates questions for a focus group. They use common abbreviations like PLS for "please" and LMK for "let me know". This is only fair because the participants use social media a lot and are likely to be tech savvy.

• RIGHT
• INCORRECT

Fairness means asking questions that make sense to everyone. Even if a data analyst suspects that people understand acronyms, jargon, or other jargon, it's important to ask questions using simple language.

Homework for week 1

question 1

Structured thinking involves which of the following processes? Select all that apply.

• Organize existing information
• Acknowledge the current problem or situation.
• Ask SMART questions
• Discover gaps and opportunities

Structured thinking involves recognizing the current problem or situation, organizing available information, discovering gaps and opportunities, and identifying options.

question 2

The preparation step of the data analysis process involves defining the problem you are trying to solve and understanding stakeholder expectations.

• RIGHT
• INCORRECT

The Ask step involves defining the problem you are trying to solve and understanding stakeholder expectations.

question 3

Which of the following activities is involved in the sharing phase of the data analysis process? Select all that apply.

• Put analytics into action to solve a problem
• Create a slideshow to present to stakeholders
• Summarize results using data visualizations
• communicate ideas

The sharing phase of the data analysis process usually involves communicating the results, summarizing the results using data visualizations, and creating a slideshow to present to stakeholders.

question 4

A garden center wants to attract more customers. A data analyst in the marketing department suggests advertising in popular landscape magazines. This is an example of which practice?

• Developing a data analysis case study
• Customer information collection
• Social media comment monitoring
• reach your target audience

This is an example of how to reach your target audience. In this scenario, people who read landscaping magazines are the target audience because they are likely interested in shopping at the garden center.

question 5

A data analyst works for a local energy company. Many new homes have been built in the community recently, so the company wants to determine how much electricity it will need to produce for new residents in the future. A data analyst uses data to help the company make a more informed forecast. This is an example of what kind of problem?

• discover something unusual
• discover connections
• identify problems
• make predictions

This is an example of predictions. Making predictions means making informed decisions about how things might turn out in the future.

question 6

Describe the main difference between the types of categorizing things and identifying problems.

• Categorizing things is determining how things are different from one another. Theme identification brings together different elements in a single group.
• Categorizing things involves assigning items to categories. Theme identification takes these categories a step further and groups them into broader themes.
• Categorizing things involves assigning ratings to items. Theme identification involves creating new classifications for items.
• Categorizing things involves taking inventory of items. Topic identification consists of creating tags for articles.

Categorizing things involves assigning items to categories. Theme identification takes these categories a step further and groups them into broader themes.

question 7

Which of the following examples are closed questions? Select all that apply.

• what do you think about math
• Is math your favorite subject?
• What grade did you get in math class?
• How old are you?

Closed questions don't encourage people to elaborate and share valuable details.

question 8

The question "Why don't our employees complete their time sheets every Friday at noon?" It is not action oriented. Which of the following questions are action-oriented and most likely to lead to change? Select all that apply.

• What features would make our timesheet website easier to use?
• What features could we add to our calendar app like a weekly timesheet reminder for employees?
• Why don't employees complete their timesheets by noon on Fridays?
• How can we simplify the time tracking process for our employees?

These questions are action-oriented. This means they are more likely to lead to specific responses that can be put into action to bring about change.

question 9

In SMART methodology, timed questions are simple, meaningful and focus on a single topic or a few closely related ideas.

• RIGHT
• INCORRECT

In SMART methodology, specific questions are simple, meaningful and focus on a single topic or a few closely related ideas.

question 10

Assumptions are made for which of the following questions? Select all that apply.

• It must be frustrating to wait that long on hold, right?
• Wouldn't you agree that product A is better than product B?
• Did you get to customer service?
• Employee engagement is important, right?

A common example of an unfair question is one that makes assumptions. Unfair questions presuppose the respondent's answer to the question.

Week 2: Make data-driven decisions

Next, we'll look at all types of data and their impact on decision-making, and learn how to share data through reports and dashboards.

In analysis, data guides decision-making. In this part of the course, you will examine data of all kinds and their implications for decision-making. You'll also learn how to share your data through reports and dashboards.

learning goals

• Discuss the use of data in the decision-making process.
• Compare and contrast data-driven decision making with data-inspired decision making
• Explain the difference between quantitative and qualitative data, including reference to their use and specific examples.
• Discuss the importance and benefits of dashboards and reports for the data analyst with reference to Tableau and spreadsheets.
• Distinguish between data and metrics and give specific examples
• Demonstrate an understanding of what is involved in using a mathematical approach to analyzing a problem.

2.1. Learn more about data-driven decisions

2.2. Understand the power of data

23. follow the evidence

2.4. Connect the data points

Answers to week two quiz questions

Video: How data enables decision-making

Fill in the blank: Data-driven decision making involves examining different sources of data to find them_.

• To escape
• Problems
• similarities
• predictions

Data-inspired decision making involves examining different data sources to find common ground.

Video: qualitative and quantitative data

Fill in the blank: Quantitative data are specific and_.

• objective
• subjective
• explanatory
• descriptive

Quantitative data is an objective, specific measure, such as B. a number, quantity, or range.

Which of the following examples would be identified using qualitative data?

• Annual precipitation in Costa Rica
• The number of passengers who take the train to go to work.
• Frequency of hurricanes per year in Louisiana
• The most popular car make and model in Puerto Rico

The most popular automobile make and model in Puerto Rico would be determined using qualitative data. Qualitative data is a subjective and explanatory measure of a quality or trait.

Video: The big reveal: share your thoughts

For which of the following scenarios would a dashboard be most beneficial?

• A project manager needs to monitor data as it becomes available.
• An analyst requires an on-demand data summary.
• A consultant needs all historical data for an audit.
• A cross-functional team needs an ad hoc update.

A dashboard would be useful to monitor data as it becomes available.

Understand the power of data

question 1

What is the difference between qualitative and quantitative data?

• Qualitative data describe the type of data analyzed. Quantitative data describes the amount of data being analyzed.
• Qualitative data are specific. Quantitative data is subjective.
• Qualitative data refer to the quality of a product or service. Quantitative data refer to how much of that product or service is available.
• Qualitative data can be used to measure qualities and properties. Quantitative data can be used to measure numerical facts.

Qualitative data can be used to measure qualities and properties. Quantitative data can be used to measure numerical facts.

question 2

Fill in the blank: Data-driven decision making is all about examining different data sources to find out_.

• how to drive business decisions
• whether they are based on facts or opinions
• What do they have in common
• how they changed over time

Data-inspired decision making is all about examining different data sources to see what they have in common.

(Video) Google Data Analytics Course Answers | All quizzes & Weekly Challenges Answers

question 3

Which of the following examples describes using data to drive business results? Select all that apply.

• A large retailer performs data analysis on product purchases to create better promotions.
• A movie theater tracks weekend viewers for three months.
• A supermarket chain collects data on items on sale and prices at each store.
• A streaming video service analyzes user preferences to personalize movie recommendations.

Analyzing user preferences to personalize movie recommendations and analyzing product purchases to create better promotions are examples of using data to drive business results. They go beyond data collection and use analytics to generate insights.

question 4

When someone describes their feelings or emotions, it is qualitative data.

• RIGHT
• INCORRECT

Qualitative data are descriptive, subjective and explanatory.

follow the evidence

question 1

Fill in the blank: Pivot tables are used in data processing tools_Data.

• people
• Sauber
• Confirm
• resume

Pivot tables are used to summarize data.

question 2

How are dashboards different from reports in data analysis?

• Dashboards contain static data. Reports contain data that is constantly changing.
• Dashboards monitor live data received from multiple datasets and organize the information in a central location. Reports are static collections of data.
• Dashboards are only used to share updates with stakeholders on a regular basis. Reports provide stakeholders with continuous access to data.
• Dashboards provide a high-level view of historical data. Reports provide a more detailed presentation of live interactive data.

Dashboards monitor live data received from multiple datasets and organize the information in a central location. Reports are static collections of data.

question 3

Describe the difference between data and metrics.

• Data can be used for measurement. Metrics cannot be used for measurement.
• Data is quantifiable. Metrics are not quantifiable.
• Data is a collection of facts. Metrics are quantifiable data types used for measurement.
• Data is quantifiable and is used for measurement. Metrics are disorganized collections of facts.

Data is a collection of facts. Metrics are quantifiable data types used for measurement.

question 4

Return on investment (ROI) uses which of the following metrics in its definition?

• profit and inversion
• supply and demand
• sales and margin
• stock and units

Return on investment (ROI) = profit/investment.

Connect the data points

question 1

Describe the main differences between small data and big data. Select all that apply.

• Small data is effective for analyzing day-to-day decisions. Big data is effective for analyzing more fundamental decisions.
• Small data are sets of data that deal with a small number of specific metrics. Big data includes larger and less specific datasets.
• Small data focuses on short, well-defined time periods. Big data focuses on changes over a long period of time.
• Small data is usually stored in a database. Big data is usually stored in a table.

Small data includes a small number of specific metrics over a shorter time period. It is effective for analyzing day-to-day decisions. Big data includes larger, less specific datasets and focuses on changes over a long period of time. It is effective for analyzing more substantive decisions.

question 2

Which of the following is an example of small data?

• Occupancy rate of hospital beds in the last ten years
• The trade deficit between two countries for a hundred years
• The total absenteeism of all high school students
• The number of steps someone takes in a day.

The number of steps someone takes in a week is an example of small data.

question 3

The amount of exercise time to burn at least 400 calories is a problem that requires big data.

• RIGHT
• INCORRECT

This problem can be solved with small data. It includes a specific metric (400 calories) and a short, defined time period (amount of exercise time).

Homework for week 2

question 1

Fill in the blank: In data analysis, there is a process or set of rules to follow for a specific task_.

• an algorithm
• a domain
• a pattern
• a value

In data analysis, an algorithm is a process or set of rules to be followed for a specific task.

question 2

Fill in the blank: In data analysis, qualitative data_🇧🇷 Select all that apply.

• measures numbers facts
• measures qualities and characteristics
• is always limited in time
• it's subjective

In data analysis, qualitative data are subjective and measure qualities and characteristics.

question 3

In data analysis, reports use live data received from multiple datasets; Dashboards use static data collections.

• RIGHT
• INCORRECT

Dashboards monitor live data received from various datasets; Reports use static data collections.

question 4

A pivot table is a data summarization tool used in data processing. Which of the following can pivot tables do? Select all that apply.

• group data
• Calculate sums of data
• clean data
• rearrange data

Pivot tables are used to reorganize, group, and calculate totals of data.

question 5

A metric is a unique, quantifiable type of data that can be used for any task.

• Define a problem type
• Set and evaluate goals.
• Sort and filter data
• clean data

A metric is a unique, quantifiable data type used to define and measure goals.

question 6

Fill in the blank: a._The objective is measurable and is evaluated through individual and quantifiable data.

• metric
• Al final
• Reference point
• conceptual

A metric goal is measurable and evaluated against discrete, quantifiable data.

question 7

When a data analyst compares the cost of an investment to the net benefit of that investment over a period of time, he is looking at the size of the investment.

• RIGHT
• INCORRECT

When a data analyst compares the cost of an investment to the net gain on that investment over a period of time, he is looking at the return on the investment.

question 8

Fill in the blank: A data analyst uses data to solve a big problem. Most likely, this type of analysis requires_🇧🇷 Select all that apply.

• small data
• Data reflecting changes over time
• Data represented by a limited set of metrics
• big data

Most likely, a data analyst using data to solve a big problem will need big data that reflects changes over time.

Week 3: Learn the basics of spreadsheets

Then we'll dive deeper into spreadsheets and how they can help make data analysis even more effective, and we'll start learning about structured thinking and how structured thinking can help analysts better understand business issues and strategies. .

Spreadsheets are an important data analysis tool. In this part of the course, you will learn why and how data analysts use spreadsheets for their work. You'll also explore how structured thinking can help analysts better understand problems and find solutions.

learning goals

• Describe key ideas associated with structured thinking, including problem domain, scope of work, and context.
• Compare formulas and functions based on similarities and differences.
• Demonstrate an understanding of how to use formulas in spreadsheets, including a definition and specific examples.
• Demonstrate using spreadsheets to perform basic data scientist tasks, including entering and organizing data.
• Discuss the data analyst's use of spreadsheets in terms of roles and responsibilities.

3.1. Introduction to worksheets

3.2. work with spreadsheets

3.3. Using formulas in worksheets

3.4. Using functions in worksheets

3.5. Save time with structured thinking

Answers to week 3 quiz questions

Video: Working with worksheets

To perform calculations in a spreadsheet, data analysts use formulas and functions.

• INCORRECT
• RIGHT

To perform calculations in a spreadsheet, data analysts use formulas and functions such as SUM, AVERAGE, and COUNT.

Video: Formulas for success

In spreadsheets, what are symbols used in formulas to perform a specific calculation called?

• references
• Attribute
• mesas
• operator

In spreadsheets, the symbols used in a formula to perform a specific calculation are called operators.

Video: Functions 101

Which of the following are characteristics? Select all that apply.

• COUNTING
• TOTAL
• START
• maximum

SUM, COUNT and MAX are functions. A function is a predefined command that uses data to automatically perform a specific process or task.

Video: Scope of Work and Structured Thinking

What process do data analysts use to understand the current situation, organize information, and identify options?

• Problems solution
• Brainstorm
• casual observation
• structured thinking

Data analysts use structured thinking to discern the current situation, organize information and identify opportunities.

Microsoft Excel Features

• Excel Quick Start Guide
• Excel-Videoschulung
• Sort data in a range or table
• Filter data in a range or table
• format a spreadsheet
• Microsoft guidelines for organizing and formatting data in a spreadsheet

Google Sheets Features

• Google Sheets Reference Sheet
• Create and import files
• Sort and filter data
• Edit and format a table
• Differences between Spreadsheets and Excel

work with spreadsheets

question 1

To sort and filter data in a table, data analysts must use several formulas.

• RIGHT
• INCORRECT

To sort and filter data in a worksheet, data analysts use worksheet sorting and filtering tools.

question 2

What time-saving tool do data analysts use to organize data and perform calculations?

• calculator
• paper
• spreadsheet
• Graphic

Data analysts use spreadsheets to organize data and perform calculations.

question 3

What tools do data analysts use in a spreadsheet to save time and effort by automating commands? Select all that apply.

• mesas
• Filter
• functions
• formulas

Data analysts use formulas and functions to save time and effort by automating commands.

Using formulas in worksheets

question 1

Which of the following are examples of operators used in formulas? Select all that apply.
1/1 point

• feature (-)
• barra (/)
• asterisk (*)
• Plus-Less (±)

The asterisk, hyphen, and slash are examples of operators used in formulas.

question 2

In a spreadsheet, a function should always start with which of the following operators?

• feature (-)
• Plus-Less (±)
• equal sign (=)
• Two points (:)

In a worksheet, a function must always start with an equals sign.

question 3

What is the term for the group of cells that a data analyst selects to include in a formula?

• cell domain
• Datengrenze
• set of cells
• data range

The set of cells that a data analyst selects to include in a formula is called a data range.

question 4

In a formula, the plus sign (+) is the addition operator and the plus-minus sign (±) is the subtraction operator.

• RIGHT
• INCORRECT

In a formula, the plus sign is the addition operator and the hyphen is the subtraction operator.

question 5

Which of the following errors can occur when cells in a table contain anything other than numbers?

• #NAME?
• #DIV/0!
• #WERT!
• #MIN/5!

If cells in a table contain anything other than numbers, you might see the message #VALUE! mistakes

Using functions in worksheets

question 1

Which of the following functions do data analysts use to quickly perform calculations in a spreadsheet? Select all that apply.

• MINIMUM
• AVERAGE
• TEMPO
• TOTAL

AVERAGE, MIN, and SUM are functions for quickly performing calculations in a worksheet.

question 2

What is the term for a predefined command in a worksheet?

• area
• Quotient
• Occupation
• cell

A standard command in a worksheet is called a function.

question 3

You are working with spreadsheet data for a cross-country relay race. The times for each runner are in cells H2 to H28. What is the correct syntax for the MIN function to find the runner with the fastest time? Enter your answer below.

=MIN(H2:H28)

Remarks: The syntax of the MIN function is =MIN(H2:H28). MIN returns the smallest numeric value in a range of cells. H2:H28 is the specified range.

question 4

A data analyst for an electronics company needs to compare the earnings of the company's four divisions over time. Collect earnings data for each unit over the last three years and create a visualization. What kind of visualization would be most effective?

• line diagram
• scatter chart
• cake plate
• infographic

A line chart would be most effective for visualizing changes over time and comparing data sets.

question 5

Which of the following charts or tables do data analysts use to visualize data? Select all that apply.

• bar graphic
• area chart
• characteristic diagram
• chord chart

Bar charts and area charts are used for data visualization.

Save time with structured thinking

question 1

Fill in the blank: To save time and money, a data analyst defines the_at the beginning of a project. Select all that apply.

• timeline
• problem domain
• important frames
• solution

To save time and money, at the start of a project, a data analyst defines the problem domain, key milestones, and timeline.

question 2

What is the name of the schema used to define a data analyst's contribution to a project?

• action plan
• Workspace
• chores
• diagram

The framework used to define a data analyst's contribution to a project is called the scope of work.

question 3

To solve a vague and complex problem, data analysts break it down into smaller steps. They use a process that helps them identify the current problem or situation. They then organize the available information, pointing out gaps and opportunities and identifying options. What process does this scenario describe?

• structured thinking
• analytical thinking
• Gap analysis
• Data-based decision making

This describes structured thinking. Structured thinking is the process of recognizing the current problem or situation, organizing available information, discovering gaps and opportunities, and identifying options. In this process, you approach a vague and complex problem by breaking it down into smaller steps, and those steps lead to a logical solution.

Homework for week 3

question 1

Both formulas and functions in spreadsheets start with which symbol?

• vertical line (|)
• equal sign (=)
• Plus minus sign (±)
• lowercase x

Both formulas and functions in worksheets begin with an equals sign.

question 2

For what purpose are attributes used in worksheets?

• Label the data in each column
• Enter data in each column
• Analyze data one by one
• Add a new column

Attributes are used to identify the type of data in each column of a table.

question 3

Which of the following tasks could be accomplished using spreadsheets?

• win a new customer
• develop communication skills
• Maintain account information.
• Write a sales pitch

A spreadsheet can be used to maintain account information.

question 4

Fill in the blank: When combining formulas and functions, the function can be executed based on a_determined by the formula.

• change
• cell
• counting
• criteria

When combining formulas and functions, the function can be executed based on the criteria specified by the formula.

question 5

Which of the following statements describes an essential difference between formulas and functions?

• Formulas are used in graphs, functions are not.
• Formulas span two or more cells, and functions exist in a single cell.
• Formulas contain both words and numbers, and functions only contain numbers.
• Formulas are written by the user and functions are already defined.

Formulas are written by the user and functions are already defined.

question 6

Fill in the blank: Putting data in context helps data analysts eliminate_.

• Justice
• intolerance
• hang tags
• trend

Putting data in context helps data analysts remove bias.

question 7

Defining the problem domain is part of which data analysis process?

• balanced thinking
• Logical thinking
• organized thinking
• structured thinking

Defining the problem area is part of the structured thinking process.

question 8

A data analyst uses structured thinking to identify the current problem or situation. Choose the last step to structured thinking.

• identify options
• display options
• clean data
• sort data

The final step in the structured thinking process is to identify options.

Week 4: Always think of the stakeholder

Finally, we'll learn some proven strategies for managing stakeholder expectations while establishing clear communication with team members to achieve our goals.

Successful data analysts learn to balance needs and expectations. In this part of the course, you will learn strategies for managing stakeholder expectations while establishing clear communication with your team to achieve your goals.

learning goals

• Discuss communication best practices for the data analyst, including reference to office communications, conflict resolution, meeting facilitation, and status reporting.
• Discuss the importance of focusing on stakeholder expectations
• Identify general data limitations, with particular reference to speed versus accuracy and response to urgent requests.

4.1. Learn best communication practices.

4.2. Align team and stakeholder needs

4.3. communication is the key

4.4. Recognize data limitations

4.5. Optional - The Secret Ingredient in the Workplace, Teamwork

Answers to week 4 quiz questions

Align team and stakeholder needs

question 1

As a data analyst, it's important to communicate frequently. Sharing detailed notes, creating reports, and using a change log are all ways to communicate with the people who have dedicated time and resources to a project. Who are these people?

• executives
• Customer Focused Team
• interested
• subject matter experts

Stakeholders invest time and resources in a project. Sharing detailed notes, creating reports, and using a change log are all useful ways to keep them up to date.

question 2

Which of the following activities does the customer service team perform? Select all that apply.

• Share customer feedback
• Gather information about customer expectations.
• Tell others the data story
• Provide operational leadership for the company.

The customer support team gathers information, shares feedback, and sets expectations.

question 3

The human resources manager approaches a data analyst to propose a new data analysis project. The analyst has a lot of experience in HR and believes that the manager is taking the wrong approach, which will bring some problems. Select data analyst best practice.

• Complete the project however you like, but take the time to resolve any issues that may arise.
• Tell the director you're sorry but you can't work on the project.
• Respectfully explain your views and offer the director some additional information to improve the project.
• Politely explain that you are too busy to take on another project.

The analyst should respectfully explain his views and offer some additional information to the manager to improve the project.

communication is the key

question 1

To clearly communicate with stakeholders and team members, there are four main questions that data analysts ask. The first is: who is my audience? Identify the remaining three questions. Select all that apply.

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

The top four questions data analysts ask when communicating with stakeholders are: Who is my target audience? What do you already know? What do you need to know? And how can I communicate with them effectively?

question 2

You are working on a data analysis project and you hit a snag. You try to find a solution but no luck and now the project is behind schedule. The best course of action is to put in extra hours to keep looking for a solution, rather than pestering your team with the problem.

• RIGHT
• INCORRECT

The best course of action is to ask your team for help. Taking the initiative to resolve issues is a great practice, but your team is a great resource when you realize you can't come up with a solution on your own.

question 3

A colleague emailed you a question almost two days ago. You know it's going to take a while to find the answer because you need to do some research first. You're too busy to do that today. What is the best course of action?

• Please respond with a brief update, thanking the sender for their patience and letting them know when they can expect a response to their inquiry.
• Forward the email to the entire data analysis team and ask if anyone can answer the question for you.
• Delete the email. Until you can answer the question, it's not useful information anyway.
• Immediately answer your question with your best guess. The sender has waited almost 48 hours and any response is better than nothing.

The best way to respond is with a brief update, thanking the sender for their patience and letting you know when you can expect a response to your question.

question 4

What goals can data analysts achieve by focusing on stakeholder expectations? Select all that apply.

• Improve communication between teams.
• Win trust
• Understand the project objectives
• Multitasking makes you more efficient

Focusing on stakeholder expectations allows data analysts to understand project goals, improve communication, and build trust.

question 5

Setting realistic stakeholder expectations at each stage of a project might involve which of the following tasks? Select all that apply.

• Prepare a report showing stakeholders the pros and cons of the design upgrade
• Create an appropriate timeline and share it with stakeholders
• Keep problems to yourself so that those involved don't have to worry about them.
• Communicate any changes that may affect the analysis to interested parties.

Setting realistic expectations for stakeholders can include creating an appropriate timeline, communicating any changes that may affect the analysis, and producing a report describing the pros and cons of a project update.

Recognize data limitations

question 1

A data analyst was asked by a stakeholder to create a report very quickly. What strategies can the analyst employ to ensure that their work is not rushed, answers the right question, and produces useful results? Select all that apply.

• rephrase the question
• Work overtime to finish the report the next day
• Set clear deadline expectations
• summarize the problem

To ensure that their work answers the right questions and yields useful results, the data analyst must set clear expectations, outline the problem, and rephrase the question.

question 2

If the sample size is too small, some unusual responses can skew the results. To avoid this problem, data analysts try to collect a lot of data and plot trends over longer time periods.

• RIGHT
• INCORRECT

If the sample size is too small, some unusual responses can skew the results. To avoid this problem, data analysts try to collect a lot of data and plot trends over longer time periods.

question 3

Ask questions like "Does my analysis answer the original question?" and "Are there other perspectives I haven't considered?" allow data analysts to perform what tasks? Select all that apply.

• Use data to come to a strong conclusion
• Help your team make informed, data-driven decisions
• Consider the best way to share data with others
• Identify primary and secondary stakeholders

By asking questions like these, data analysts can consider how best to share data with others, help their team make informed decisions, and use the data to reach a solid conclusion.

The secret ingredient in the workplace, teamwork.

question 1

Your manager gives you a new data analysis project with unclear instructions, and you're frustrated trying to figure out how to proceed. What must you do before continuing? Select all that apply.

• Go to your manager personally so he understands exactly how stressed you feel.
• Do additional research to better understand the context of the request.
• Take a few minutes to calm down and ask your manager more questions to learn more about the big goals.
• Email your manager and say the project wasn't explained well to you.

Doing additional research and asking questions are effective ways to determine how to proceed with a new project.

question 2

You are working on a data analysis project with a colleague and you both disagree with what the data is saying. Things get tense. The best thing to do is go to your manager and politely explain that your colleague is looking at the data incorrectly. Then ask to work with another colleague on future projects.

• RIGHT
• INCORRECT

Discussion is the key to conflict resolution. When you're in the middle of a conflict, strike up a conversation so you can explain your concerns and find the best way forward.

question 3

A director will send an email requesting a report by the end of the week. It takes at least 10 days to successfully complete this type of report. What is the best course of action?

• Complete the report as best you can by the end of the week to meet the required deadline.
• Forward the email to another data analyst on your team and ask them to create the report for you. It will be late, but at least it won't reflect badly on you.
• Email the director and tell him you'd like to do this, but you think it will take 10 days to get the information you need. Then ask if you can discuss the possibility of a different time.
• Call the director and let him know that no one can meet this deadline.

The best course of action is to email the Director to politely explain the timeframe needed to successfully complete the report.

(Video) Google Data Analytics Quiz | Itronix Solutions | Exam Answers

Homework for week 4

question 1

A data analytics team works on a project to measure the success of a company's new financial strategy. Most likely, the vice president of finance_.

• project manager
• Analyst
• secondary participant
• hero

Most likely, the VP of Finance is the primary stakeholder.

question 2

A data analyst examines the buying behavior of people who shop at a company's retail store and people who might shop there in the future. During the review, it's important to stay in touch with the team that interacts most with these buyers. What is the name of this team?

• project management team
• leadership team
• data science team
• Customer Focused Team

Customer-facing staff include anyone in an organization who interacts with customers or potential customers, such as shoppers in a company's retail store.

question 3

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

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

The top four questions data analysts ask when communicating with stakeholders are: Who is my target audience? What do you already know? What do you need to know? And how can I communicate with them effectively?

question 4

A data analyst feels overwhelmed. Often, they were late to finish work and started to miss deadlines. The manager sends an email with another project to complete, adding even more stress to the analysts. How should they handle this situation?

• Please respond immediately and tell the manager that the expectations placed on this company are unreasonable.
• Embrace the new project right away and hope you don't miss another deadline.
• Go to the supervisor's office and tell him to give the project to someone else.
• Take a few minutes to think about it, then respond with a meeting request to discuss this project and general workload.

You should take a few minutes to think about it, then respond with a meeting request to discuss this project and general workload. When people are angry or emotional, it's best to wait until things calm down. Then give everyone a chance to share their thoughts.

question 5

Data analysts pay attention to sample size to achieve what goals? Select all that apply.

• To ensure that some unusual responses do not skew the results
• To ensure the data represents a variety of perspectives
• To prevent a small sample size from leading to inaccurate judgments
• Fully understand the scope of the analysis project.

Data analysts pay attention to sample size to present a variety of perspectives and avoid biased results or inaccurate judgments.

question 6

A data analyst has been invited to a meeting. You review the agenda and notice that your data analysis project is one of the topics covered. You plan to be on time and have a pen and paper to take notes. But they don't spend time thinking of project updates to share or questions to ask. That's okay because you're not the one running the meeting.

• RIGHT
• INCORRECT

Even if the data analyst isn't chairing the meeting, it's a good idea to be prepared to share updates and answer questions when your project is on the agenda. This helps keep everyone in the loop and ensures effective communication.

question 7

Which of the following steps are essential for holding a professional meeting online? Select all that apply.

• Keep control of the meeting by muting everyone else.
• Sit in a quiet environment free from distractions
• Keep an eye on your inbox during the meeting in case you receive an important email
• Make sure your technology is working properly before starting the meeting

When hosting an online meeting, acting professionally means encouraging others to contribute, testing the technology beforehand, and eliminating distractions.

question 8

Conflict is a natural part of teamwork. What are the possibilities of turning a problematic situation into a productive one? Select all that apply.

• Identify the person who caused the problem so they can take responsibility.
• Request a conversation to better understand the big picture.
• Before getting into an argument, take a moment to examine your feelings.
• Reframe the question by asking, "How can I help?"

To turn a problematic situation into a productive one, rephrase the question, control your emotions, and establish open lines of communication.

natural challenge

Scenario 1, Questions 1-5

question 1

You've just started a job as a data analyst at a small software company that provides data analytics and business intelligence solutions. Your manager asks you to start a project with a new client, Athena's Story, a feminist bookstore. He has four existing locations and the fifth store has just opened in his community.

Athena's Story wants to produce a campaign to build excitement for an upcoming celebration and introduce the bookstore to the community. Share some data with your team to make the event as successful as possible.

Your job is to review the task and available data, then present your approach to your manager.

Then review the email and customer survey and sales history records:

• You can click on the link to make a copy of the dataset: Customer Survey
• You can click on the link to make a copy of the historical sales record

After reading the email, you will notice that WHM appears in several places. Search online and the most common result is web hosting manager. This doesn't seem right to you because it doesn't fit the context of a feminist bookstore.How do you proceed?

• Call the customer to ask what WHM stands for and let them know that the use of acronyms is not a professional business practice.
• Go ahead with the project and assume that WHM should stand for web hosting manager.
• Schedule a meeting with your manager, the customer, and another analyst on your team to find out what this means.
• Send your manager a polite and concise email asking him to recognize the importance of OHM.

You should send your manager a polite and concise email asking him to confirm the importance of WHM.

question 2

Scenario 1 continuation
Now that you know WHM stands for Women's History Month, keep checking the records. You can see that the customer survey dataset contains both qualitative and quantitative data.

Qualitative data contains information from which columns? Select all that apply.

• Column B (Survey Q2: If you answered yes to Q1, how do you plan to celebrate?)
• Column F (Survey Q6: What types of books would you like to see more of in The Story of Athena?)
• Column E (Survey Q5: What do you like most about the Athena story?)
• Column D (Survey Q4: If the answer to question 3 is yes, how many books do you usually buy in March?)

Qualitative data includes information from columns B, E, and F.

question 3

Then review the customer feedback in column F of the customer survey (CSV file download link below).
Customer Survey – Customer Survey.csv

The attribute in column F is: "Poll Q6: What kind of books would you like to see more of in The Story of Athena?" To see whether children's literature and feminist magazines are among the most popular genres, create a visualization. This will help you clearly see which genres are most likely to sell during your Women's History Month campaign.

Your view looks like this:

Fill in the blank: The visualization you created shows the percentages of each book genre that make up the total number of survey responses. It's called graph _.

• pastel
• area
• from the
• Tired out

The visualization is called a pie chart.

question 4

Now that you've confirmed that children's literature and feminist magazines are among the most sought-after book genres, check out Historical Sales.

You are pleased to see that columns D and E have something in common: they both contain data specific to children's literature and feminist journals. This gives you the information you need to make data-driven decisions. In addition, metrics for children's literature and feminist journals help you organize and analyze the data for each genre to determine whether it is likely to be profitable.

You will then use the SUM function to calculate the total 52-week sales of women's magazines. What is the correct syntax? Enter your answer below.

=SUMA(E2:E53)

The correct syntax is =SUM(E2:E53). The SUM function sums the values ​​in a range of cells. E2:E53 is the specified range.

question 5

Once you've familiarized yourself with the project and the available data, present your approach to your manager. It provides a scope of work that includes key details, a timeline, and how you plan to prepare and validate the data. He also shares some of his first results and the pie chart he created.

Also, identify the type of problem or domain for the data analysis project. They decide that historical sales data can be used to provide insight into the types of books that will be best sellers during Women's History Month next year. This will also help you decide whether Athena's Story should start selling more children's literature and feminist magazines.

Using historical data to make informed decisions about how things might be in the future is an example of discovering connections.

• RIGHT
• INCORRECT

Using historical data to make informed decisions about how things might be in the future is an example of forecasting.

Scenario 2, questions 6-10

question 6

You have completed this program and are now applying for your first position as a Junior Data Analyst. They hope to be hired by an event planning company, Patel Events Plus.

So far you have successfully completed the first round of interviews with the Human Resources Manager and the Director of Data and Strategy. Now the VP of data and strategy wants to know more about your approach to project and customer management.

You arrive on Thursday at 1:45 pm for your interview at 2 pm. You will shortly be taken to the office of Mila Aronowicz, Vice President of Data and Strategy. After greeting him, the behavioral interview begins.

First, he hands you a copy of the Patel Events Plus org chart.

As you learned in this course, stakeholders are people who invest time, interest, and resources in the projects you work on as a data analyst. Let's say you're working on a project that involves data and strategy.Based on what you can find in the org chart, if you need secondary stakeholder information, who can you contact? Select all that apply.

• Project Manager, Analysis
• Vice President, Data and Strategy
• General Manager
• Data Analysis Coordinator

If you need information from secondary stakeholders, you can ask the project manager and data analysis coordinator.

question 7

Next, the VP wants to understand your knowledge of how to ask effective questions. Think about and answer the following question. Select all that apply.

Let's say we've just completed a big event for a client and we want to know how happy you were with your experience. Please provide some examples of measurable questions you can include in your customer feedback survey.

• Why did you like the event planned by Patel Events Plus?
• Would you recommend Patel Events Plus to a colleague or friend? Yes or no?
• Please rate your satisfaction with the event we have planned for you on a scale of 1 to 5.
• How would you describe your experience at the event?

In SMART methodology, measurable issues can be quantified and evaluated. This may include a 1-to-5 scale or yes/no questions.

question 8

Now the vice president presents a situation related to solving challenges and meeting stakeholder expectations. Think about and answer the following question.

You are working with a dataset that the data analysis coordinator should have cleaned but didn't. Your manager thought the dataset was ready, but discovered nulls, redundant data, and other issues. The project must be delivered in less than two weeks. How would you handle this situation?

• Contact the Associate Data Analyst and insist that he clean up the data set immediately so you don't miss the project deadline.
• Call a formal meeting with the data analytics team to resolve the issue. Please do not invite the associated data analyst as he clearly does not have time to help.
• Send an email to your manager to inform him that the Associate Data Analyst did not complete the assigned task.
• Contact the Associate Data Analyst about the issue and offer to help clean up the data so the project doesn't fall behind.

This situation presents an opportunity to communicate, collaborate and promote positive working relationships.

question 9

Your next interview question is about sharing information with stakeholders. Think about and answer the following question.

Suppose you want to share information about an upcoming event with interested parties. It's important that they can access and interact with the data in real time. Would you create a report or a dashboard?

• quadro
• Message

Dashboards provide live monitoring of incoming data and allow stakeholders to interact with the data.

question 10

Your final interview behavior question involves using metrics to answer business questions. Your chat partner provides a copy of PatelEventsData.

Then she asks:

Patel Events Plus recently purchased a new location for our events.If we asked you to calculate the ROI of this purchase, which metric would you use?

• date from purchase
• 2019 events at the new headquarters (column D)
• Net income 2019 (column F)
• Purchase price (column C)

ROI is made up of two metrics: net income over a period of time and cost of investment. By comparing these two metrics, you can determine your return on investment.

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