harnessing the power of data with power bi coursera week 3 answers
Self-review: Product launch analysis
1. Which data type in Microsoft Excel is most appropriate for the Product Price field in the Adventure Works sales dataset?
- Short date
- Currency
- Scientific
- Text
2. What is the primary risk of not properly cleaning and preparing the data for analysis at Adventure Works?
- Adventure Works’ data storage costs may increase.
- Adventure Works’ data infrastructure could be compromised.
- Adventure Works will have to put the product launch on hold.
- Adventure Works could make poor decisions related to the product launch.
3. What is the most appropriate method for handling missing entries in the Product Description column in the Adventure Works sales dataset using Microsoft ExceI?
- Copy the Product Description from a similar product.
- Leave the missing entries unchanged.
- Use the last updated Product Description to fill in the missing entry.
- Remove the rows with missing entries for the Product Description.
4. In the Adventure Works sales dataset, which data field would you primarily analyze to understand sales trends over time?
- Order Date
- Customer ID
- Product Weight
- Payment Method
5. Which type of additional data could supplement the sales analysis by providing insights into what customers like or dislike about Adventure Works' products?
- Order details
- Supply chain data
- Website analytics
- Feedback data
Course Quiz: Harnessing the Power of Data in Power BI
6. Imagine you are a data analyst at Adventure Works, hired to strengthen decision-making in the company. Which statement best reflects your primary responsibility as a data analyst in the organization?
- Your main role as a data analyst is to create a data model representing the structure and relationships of the data.
- Your main role as a data analyst is to conduct market research and develop social media strategies and campaigns.
- Your main role as a data analyst is to manage Adventure Works’ IT infrastructure and data security.
- Your main role as a data analyst is to collect, organize, and analyze data to generate insights.
7. As a data analyst, you need to share your data insights with relevant stakeholders. What best practice can you implement to ensure the data used for your data analysis and reports is up-to-date and reliable?
- Ensure your data reports are secure and accessible only to authorized users
- Ensure accessibility and device compatibility for your data reports
- Regularly consider data storage and refresh schedules for your data reports
- Consider the design and visual appeal of your data report, including color schemes and fonts
8. What is the primary role of data in the data analysis process?
- Data is collected, cleaned, processed, and interpreted to extract insights and inform decisions.
- Data is solely used for troubleshooting technical issues.
- Data is primarily used to test the functionality of data analysis software.
- Data provides a basis for the company’s annual reports.
9. What non-technical skills are essential for a data analyst to succeed in their role? Select all that apply.
- Using statistical analysis software
- Awareness of impact
- Strategic thinking
- Understanding of context
10. You are a data analyst for Adventure Works, a company that collects large amounts of data from various sources. How can you use Microsoft Power Query to perform efficient data analysis? Select all that apply.
11. What is the primary responsibility of a Data Engineer in the data analysis process?
12. In the context of data analysis, which statements accurately describe the concept of diplomacy as a non-technical skill? Select all that apply.
- Communicating with stakeholders to identify their needs and preferences in relation to the data analysis.
- Navigating sensitive situations related to data analysis and maintaining positive relationships with stakeholders.
- Proficiency in explaining advanced predictive modeling and data visualization techniques to stakeholders.
- Mediating disagreements among stakeholders related to data interpretation or decision-making.
13. How can a data analyst better understand the needs of end-users?
- By learning more programming languages to cater to different business problems.
- By attending more technical workshops.
- By asking questions, empathizing with the users’ perspectives, and collaborating with stakeholders.
- By reading more data analysis and business books.
14. As a data analyst at Adventure Works, you're part of a project to improve operational efficiency. The team comprises individuals from diverse backgrounds—logistics, finance, IT, and customer service. How would your role as a 'translator' be beneficial in this scenario?
- By converting raw data into visually appealing and intricate charts and diagrams.
- By retaining control of all data tasks, reducing the need for others to understand complex concepts.
- By explaining data insights in a simple, understandable way to aid communication.
- By understanding the specific jargon and technical language of each department.
15. Data preparation is crucial for the data analysis process. Which of the following are the objectives of data preparation? Select all that apply.
- Gathering, cleaning, and pre-processing raw data to make it suitable for analysis.
- Digging deep into data to uncover insights and answer specific questions.
- Creating a data model that represents the structure and relationships of the data.
- Identifying inconsistencies and errors in the data.
16. As a data analyst at a retail store, you're asked to define the scope of your data. What could this involve? Select all that apply.
- Determining the time frame for your analysis.
- Deciding on the geographical regions you are interested in.
- Selecting the product categories you want to include.
- Identifying the type of data to be collected.
17. In data analysis, what is the purpose of data preparation? Select all that apply.
- Making sure that the data is consistent.
- Identifying the sources of data.
- Ensuring that the data is accurate.
- Getting the data ready for analysis.
18. In the data analysis process, what is the primary purpose of the ETL (Extract, Transform, Load) process? Select all that apply.
- Consolidating data from multiple sources into a single source for easy access.
- Performing complex calculations on the data.
- Loading the transformed data into a suitable storage space.
- Transforming raw data into a structured format suitable for analysis.
19. Adventure Works is planning significant changes to its manufacturing system. You are responsible for analyzing large amounts of complex data and presenting your findings to the company executives. How can data visualization contribute to your work?
- Data visualization can help support gathering manufacturing data from various sources, ensuring comprehensive understanding.
- Data visualization can replace the need to analyze manufacturing data, improving efficiency.
- Data visualization can validate the accuracy of the manufacturing data and the reliability of the analysis.
- Data visualization can help make the manufacturing data more accessible to stakeholders and easier to understand.
20. Adventure Works collected data from various markets around the world. You need to analyze this data to guide the company's expansion strategy. The stakeholders include the marketing team, product managers, executives, and external partners. Given the diversity and varying levels of data literacy among the stakeholders, why is understanding their experience critical when it comes to data visualization?
- It assists in gathering more data for future analysis, ensuring a more comprehensive range of insights.
- It assists in determining the appropriate file formats for sharing visualizations.
- It helps create effective visualizations leading to better decision-making.
- It helps to identify optimal color schemes and font styles to use in the visualizations.
21. As Adventure Work's business operations continue to expand, there has been a significant increase in the volume of data generated from various internal and external sources. As their data analyst, how can you use Microsoft Power Query Editor in Microsoft Power BI Desktop?
- To forecast future sales trends based on historical data.
- To automate the data collection process from various sources.
- To create a detailed data model of the entire company operations.
- To clean, transform, and reshape data for analysis.
22. Your manager tasks you, a data analyst, with creating a series of complex calculations in Microsoft Power BI. Using the code snippet and screenshot as a guide, what language is most appropriate for this task?
1 AverageSales = CALCULATE(AVERAGE(Sales[Order Total]))
- SQL
- R
- Python
- Data Analysis Expressions (DAX)
23. Your manager asks you to classify different data sets as a data analyst. Which of the following can you classify as semi-structured data? Select all that apply.
- Data stored in a software platform, such as an Enterprise Resource Planning (ERP) system.
- Data collected from automatic door sensors.
- Data from customer feedback forms.
- Images and videos coming from social media.
24. Adventure Works has a team of field sales representatives who are always on the move. As a data analyst, your manager asks you to give stakeholders real-time access to reports and dashboards on their mobile devices. Which component of Power BI is specifically designed for this purpose?
- Power BI Apps
- Power BI Connectors
- Power BI Report Server
- Power BI Embedded
25. You're a data analyst at Adventure Works. You recently created a report in Power BI Desktop, published it to the Power BI Service, and created dashboards. What actions would you perform as a part of the final Share step in your workflow? Select all that apply.
- Apply different user permission levels to your dashboards to manage access data access.
- Share your data with relevant stakeholders to promote collaboration.
- Analyze and present your data using various visualizations and charts.
- Use Power BI Mobile apps to view and interact with the report and dashboards.
26. Your manager asks you to create a series of visualizations as part of a presentation to the board of directors at Adventure Works, who have a wide range of technical expertise. What influence will this have on your task?
- Stakeholders’ technical expertise determines which data sources you should use for the visualizations included in the dashboard.
- Stakeholders’ technical expertise influences the complexity and depth of the visualizations.
- Stakeholders’ technical expertise primarily guides the theme choices for the dashboard, ensuring visual appeal.
- Stakeholders’ technical expertise limits the choice of visualizations to simple charts.
27. What is the benefit of automating data ingestion processes?
- It processes data for storage in a database.
- It can enhance operational efficiency and reduce manual labor.
- It allows for the ingestion of structured data.
- It decreases the variety of data types that can be ingested.
28. You are a data analyst discussing the manual data entry method of data ingestion with your team. Which of the following are the limitations of this method? Select all that apply.
- It does not allow for the ingestion of structured data.
- It is time-consuming and prone to errors.
- It is unsuitable for large-scale data ingestion.
- It requires specialized tools and infrastructure to handle the continuous flow of data.
29. At Adventure Works, you need to extract, transform, and load data from various data sources to consolidate them into the company's data warehouse. What critical elements will you focus on during the Transform step of the Extract, Transform, Load (ETL) process?
- Prioritizing real-time data ingestion over batch processing.
- Ensuring the transformed data is consistent, accurate, and complete.
- Implementing machine learning models for predictive analysis.
- Organizing file structure for data accessibility.
30. The Adventure Works data analytics team evaluates the current data storage system for possible upgrades. You need to assess the system's scalability. What will you evaluate the system for?
- Its ability to provide remote access to data.
- Its ability to integrate new data sources.
- Its ability to handle changes in data volume.
- Its ability to store data in different formats.
31. What is the primary advantage of cleaning data at the source?
- It ensures that future analyses have a clean and consistent foundation.
- It changes the data format to make it more suitable for analysis.
- It facilitates duplicate data entries in the analysis.
- It allows for transforming data within the Microsoft Power BI environment.
32. What is the primary purpose of using data validation in Excel while cleaning data?
- To extract specific parts of text from a cell.
- To find and retrieve data from other parts of the worksheet.
- To apply different formats to cells based on specific conditions.
- To set criteria for the allowable data in a cell or range of cells.
33. Imagine you are a Data Analyst at Adventure Works using Microsoft Power Query to transform raw sales data into a more usable format. The transformation involves multiple steps, like removing duplicates, filtering rows, and replacing values. What are some of the functionalities of the Applied Steps pane? Select all that apply.
- To record the transformation steps in data preparation.
- To clean, reshape, and transform data into a structured, usable format.
- To connect various data sources and select specific datasets or tables.
- To show the history of actions performed on the dataset.
34. Your team at Adventure Works is working on a new project to analyze customer feedback. The feedback comes from various channels and in multiple formats. As a data analyst, you're asked to transform this data using Microsoft Power BI. What is the primary objective of data transformation in Power BI?
- To facilitate real-time collaboration with team members.
- To create meaningful and impactful data visualizations.
- To automate the process of data entry.
- To convert raw data into a more meaningful and usable format.
35. Regarding data management in Microsoft Power BI, what does cleaning data at the source involve? Select all that apply.
- Refining and correcting your data in the original source before importing it into a tool for further analysis or visualization.
- Evaluating your Power BI reports and identifying and addressing any errors, such as inconsistencies in the data visualizations.
- Checking data consistency and removing duplicates at the source before importing it to Power BI.
- Importing data in Power BI for visualization by retrieving and integrating data from multiple sources.
36. What is the primary reason for considering storage and refresh schedules in data reports?
- To ensure users always work with up-to-date information.
- To make the reports look more professional.
- To reduce the amount of data stored.
- To prevent unauthorized access to the data.
37. In the process of data analysis, how is data used? Select all that apply.
- Data is collected, cleaned, processed, and interpreted to extract insights and inform decisions.
- Data provides a basis for the company’s annual reports.
- Data is primarily used to test the functionality of data analysis software.
- Data is solely used for troubleshooting technical issues.
38. Which non-technical skill is crucial for data analysts?
- Data visualization
- Strategic thinking
- Data wrangling
- Using statistical analysis software
39. In data analysis, what is Power Query primarily used for?
- To stream data in real time, enabling immediate data processing and analysis.
- To create visually appealing and interactive data visualizations for analysis reports.
- To connect to data sources, clean and transform data, and load it into Microsoft Power BI.
- To create comprehensive business reports with insights for data-driven decision-making.
40. Adventure Works plans to expand its product line and market reach. Imagine you're a Data Engineer and you need to service the existing data infrastructure to handle the anticipated increase in data volume and complexity. Which statement best describes your primary responsibility in this role?
- Conduct competitive market research to gain insights into potential business opportunities.
- Coordinate with the sales team to implement new sales strategies based on data insights.
- Liaise with vendors and negotiate the purchase of new hardware and software.
- Design, construct, and maintain the data infrastructure.
41. Imagine you are a data analyst working at Adventure Works. Your stakeholders have varying levels of data literacy and often have conflicting opinions about data interpretations. You often find yourself in the middle of these discussions as a data analyst. in your role, which statement best describes the application of diplomacy as a non-technical skill?
- Modify your data analysis results to align with the preferences of each stakeholder.
- Take charge of all business operations influenced by your data insights.
- Managing disagreements and maintaining trust and respect even when presenting challenging results.
- Generate multiple versions of your analysis to accommodate stakeholder perspectives.
42. What actions can help you better understand end-user needs as a data analyst? Select all that apply.
- Asking questions, empathizing with the users’ perspectives, and collaborating with stakeholders.
- Learning more programming languages to cater to different business problems.
- Attending more technical workshops.
- Frequently engaging with users to get feedback on the data analysis results.
43. What does being a successful 'translator' in the context of a Data Analyst mean?
- Skill in translating raw data into visual graphs.
- The ability to translate complex concepts into easily understandable terms.
- The ability to work with multiple programming languages.
- Competence in translating foreign languages.
44. What is the primary purpose of the ETL (Extract, Transform, Load) process in data analysis?
- To transform raw data into a structured format suitable for analysis.
- To perform complex calculations on the data.
- To consolidate data from multiple sources into a single source for easy access.
- To create visualizations of the data.
45. Why is data visualization important in the data analysis process?
- It helps in extracting data from various sources.
- It helps make complex data more accessible and easier to understand.
- It ensures the accuracy of the data.
- It replaces the need for complex calculations.
46. Why is understanding stakeholder experience critical in data visualization? Select all that apply.
- It helps create effective visualizations that lead to better decision-making.
- It can help by increasing collaboration and leading to improved business outcomes.
- It reduces the time required for visualization design.
- It is necessary for compliance with data regulations.
47. As a Data Analyst at Adventure Works, you're preparing to lead a training session for a group of new hires on a set of key tools within the Power BI suite. How would you explain the primary use of Power Query Editor, the tool in the screenshot?
- It allows you to share and collaborate on reports and dashboards.
- It allows you to clean, transform, and reshape data.
- It allows you to filter data at various levels.
- It allows you to visualize data with bar charts and maps.
48. You are creating calculations in Microsoft Power BI. Which languages are supported in Power BI to perform this task? Select all that apply.
- Data Analysis Expressions (DAX)
- R
- SQL
- Python
49. You are working on a project evaluating customer feedback from various sources. How should you classify customer feedback forms consisting of ratings and written comments?
- Structured data
- Unstructured data
- Semi-structured data
- Transformed data
50. Why is it important to consider the technical expertise of stakeholders as a part of the data visualization process?
- It influences the complexity and depth of the visualizations.
- It determines the color scheme of the visualizations.
- It determines the aesthetics and formatting of the visualizations.
- It helps in deciding the number of visualizations to be created.
51. What is a limitation of the manual data entry method of data ingestion?
- It requires specialized tools and infrastructure to handle the continuous flow of data.
- It can only be used with databases or data warehouses.
- It does not allow for the ingestion of structured data.
- It is time-consuming and prone to errors.
52. A colleague asks you about the Transform step in the Extract, Transform, Load (ETL) process. What are the critical elements to ensure during this step? Select all that apply.
- Organizing file structure for data accessibility.
- Ensuring the transformed data is consistent, accurate, and complete.
- Ensuring data is accessible for legal purposes.
- Cleaning the extracted data.
53 Your colleague asks you to help clarify the concept of scalability in the context of data storage planning. What does scalability typically refer to? Select all that apply.
- The ability to securely store data for legal purposes.
- The ability to handle increased or decreased data volume as the organization grows.
- The ability to maintain performance levels with increasing data loads.
- The ability to provide remote access to data.
54. You are having a conversation with a co-worker about the advantages of cleaning data at the source. What benefits can this practice offer? Select all that apply.
- It ensures that future analyses have a clean and consistent foundation.
- It reduces the likelihood of inconsistencies and errors in the data.
- It allows for data transformation within the Microsoft Power BI environment.
- It facilitates duplicate data entries in the analysis.
55. What is the purpose of the Applied Steps pane in Microsoft Power Query?
- To record the transformation steps in data preparation.
- To provide a list of data sources.
- To display the final data visualization.
- To perform mathematical calculations on data.
56. You're working on a Microsoft Power BI project. What are the main objectives of data transformation? Select all that apply.
- To convert raw data into a more meaningful and usable format
- To perform mathematical calculations on data.
- To reduce the size of the data set.
- To improve data quality and consistency.
57. Imagine you are a data analyst for Adventure Works. What is your responsibility in relation to generating data insights that the company can use to make data-driven decisions? Select all that apply.
- To understand the context in which you are working, including the industry, market trends, and company goals
- To collect data from multiple sources and organize the data in preparation for analysis
- To analyze customer behavior and identify trends that can inform marketing campaigns
- To implement marketing and social media engagement strategies to improve sales
58. What are the main uses of Microsoft Power Query in data analysis? Select all that apply.
- To connect to data sources, clean and transform data, and load it into Microsoft Power BI.
- To stream data in real time, enabling immediate data processing and analysis.
- To create visually appealing and interactive data visualizations for analysis reports.
- To automate data preparation tasks, such as data extraction, cleaning, merging, and transformation.
59. You're a data analyst at Adventure Works who needs to analyze year-over-year sales growth. What should you do to define the scope of your data for this task?
- Start the process of cleaning and preparing the data for data analysis.
- Include as many data sources and datasets in your analysis as possible to ensure comprehensive insights.
- Define the years, geographical regions, and product categories to include in the analysis.
- Identify the data type to be collected and extract the data from the relevant sources.
60. As a data analyst at Adventure Works, your manager assigns you a project to analyze sales data from the North American market. What should be your primary focus during the data preparation stage?
- Ensuring the data is accurate, consistent, and ready for analysis.
- Sharing the raw data with the stakeholders for their input.
- Identifying any insights or trends in the data.
- Conducting a preliminary data analysis to get a general overview.
61. You're a data analyst at Adventure Works and have to work with various manufacturing data sources. Your manager asks you to use the ETL (Extract, Transform, Load) process to prepare the data. What would be the primary goal of using this process?
- To transform the raw manufacturing data into a structured format suitable for analysis and load it into a suitable storage space.
- To encrypt the manufacturing data to ensure privacy and security.
- To conduct a preliminary analysis of the manufacturing data.
- To consolidate all the manufacturing data into a single file for easy access.
62. As a data analyst, you work with the Microsoft Power Query Editor in Microsoft Power BI Desktop. What are some of the core functionalities provided by the Power Query Editor? Select all that apply.
- It allows you to merge and append queries.
- It permits you to visualize data using bar charts and maps.
- It enables you to clean, transform, and reshape data.
- It provides a platform to share and collaborate on reports and dashboards.
63. Which of the examples of data can you classify as semi-structured data?
- Data stored in a software platform like an Enterprise Resource Planning (ERP) system.
- Images and videos coming from social media.
- Data collected from automatic door sensors.
- Sales revenue figures
64. Which Microsoft Power BI components allow you to view and interact with reports and dashboards from mobile devices? Select all that apply.
- Power BI Apps
- Power BI service
- Power BI Connectors
- Power BI Desktop
65. Why is the technical expertise of stakeholders essential when creating data visualizations? Select all that apply.
- It influences the complexity and depth of the visualizations.
- It determines the color scheme of the visualizations.
- It guides the choice of appropriate visualization tools and techniques.
- It helps in deciding how many visualizations to create.
66. At Adventure Works, your manager tasks you with ensuring the integrity of data entered into a shared Excel workbook used for an ongoing project. Why would you use data validation rules in Excel to control the input and maintain data quality?
- Excel data validation rules make linking cells across different worksheets easier.
- Data validation rules in Excel help automate the calculation process.
- Data validation rules in Excel allow you to set criteria for the allowable data in a cell or range of cells.
- Data validation rules in Excel enable real-time collaboration.
67. You are using Microsoft Power Query for data transformation. What functionalities does the Applied Steps pane offer you? Select all that apply.
- It provides a list of data sources.
- It records the transformation steps in data preparation.
- To show the history of actions performed on the dataset.
- It displays the final data visualization.
