WGU D553: Data Analytics for Accountants II|Explore New 120
Questions and Answers|New 2025 Update with complete
solution|Study tips 100% Correct
Section 1: Foundations of Data Analytics in Accounting
1. What is data analytics in accounting?
Analyzing financial and operational data to uncover insights for decision-making.
2. Why is data analytics important for accountants?
It helps identify trends, improve accuracy, detect fraud, and enhance decision-making.
3. What are the four types of data analytics?
Descriptive, diagnostic, predictive, and prescriptive analytics.
4. What is descriptive analytics?
A method of analyzing historical data to understand past performance.
5. What is diagnostic analytics?
Investigating why something happened in the data.
6. What is predictive analytics?
Using statistical techniques to forecast future outcomes.
7. What is prescriptive analytics?
Recommending actions based on predictive analytics.
8. What are key performance indicators (KPIs) in accounting?
Metrics used to measure performance against specific objectives.
9. What is the role of dashboards in analytics?
They provide a visual representation of key metrics and trends.
10. What is metadata?
Data that describes other data, such as file type, size, and creation date.
11. What is the difference between structured and unstructured data?
Structured data is organized in rows and columns; unstructured data includes emails,
social media, and images.
12. What is the difference between quantitative and qualitative data?
Quantitative data is numerical, while qualitative data is descriptive and categorical.
13. What are the main sources of accounting data?
Financial statements, ERP systems, transaction logs, and external reports.
14. What is big data in accounting?
Large and complex datasets analyzed to identify trends, patterns, and insights.
15. What is the difference between real-time and batch data processing?
Real-time processing handles data instantly, while batch processing handles it at
intervals.
, Section 2: Data Preparation and Cleaning
16. What is data cleaning?
Removing inaccuracies, duplicates, and inconsistencies in data.
17. Why is data cleaning important?
Ensures accuracy, reliability, and validity of analysis results.
18. What is data wrangling?
Transforming raw data into a usable format for analysis.
19. What is ETL in data analytics?
Extract, Transform, Load: A process for preparing data for analysis.
20. What is data normalization?
Organizing data to reduce redundancy and improve integrity.
21. What is data enrichment?
Enhancing existing data by adding relevant external data sources.
22. What is missing data imputation?
Techniques to handle missing data, such as mean substitution or regression imputation.
23. What is a data dictionary?
A document that describes the structure, content, and format of data.
24. What is data deduplication?
Identifying and removing duplicate records.
25. What is data integrity?
Ensuring data is accurate, consistent, and reliable.
Section 3: Advanced Excel for Accountants
26. What is a pivot table in Excel?
A tool for summarizing and analyzing large datasets.
27. What is conditional formatting in Excel?
A feature that changes cell appearance based on specific criteria.
28. What is the VLOOKUP function in Excel?
A function to search for a value in a column and return data from the same row.
29. What is a macro in Excel?
A script that automates repetitive tasks.
30. What is the purpose of slicers in Excel?
Interactive buttons that filter data in pivot tables or charts.
Here is the continuation of 200 questions and answers for WGU D553: Data Analytics for
Accountants II.
Section 3: Advanced Excel for Accountants (continued)
Questions and Answers|New 2025 Update with complete
solution|Study tips 100% Correct
Section 1: Foundations of Data Analytics in Accounting
1. What is data analytics in accounting?
Analyzing financial and operational data to uncover insights for decision-making.
2. Why is data analytics important for accountants?
It helps identify trends, improve accuracy, detect fraud, and enhance decision-making.
3. What are the four types of data analytics?
Descriptive, diagnostic, predictive, and prescriptive analytics.
4. What is descriptive analytics?
A method of analyzing historical data to understand past performance.
5. What is diagnostic analytics?
Investigating why something happened in the data.
6. What is predictive analytics?
Using statistical techniques to forecast future outcomes.
7. What is prescriptive analytics?
Recommending actions based on predictive analytics.
8. What are key performance indicators (KPIs) in accounting?
Metrics used to measure performance against specific objectives.
9. What is the role of dashboards in analytics?
They provide a visual representation of key metrics and trends.
10. What is metadata?
Data that describes other data, such as file type, size, and creation date.
11. What is the difference between structured and unstructured data?
Structured data is organized in rows and columns; unstructured data includes emails,
social media, and images.
12. What is the difference between quantitative and qualitative data?
Quantitative data is numerical, while qualitative data is descriptive and categorical.
13. What are the main sources of accounting data?
Financial statements, ERP systems, transaction logs, and external reports.
14. What is big data in accounting?
Large and complex datasets analyzed to identify trends, patterns, and insights.
15. What is the difference between real-time and batch data processing?
Real-time processing handles data instantly, while batch processing handles it at
intervals.
, Section 2: Data Preparation and Cleaning
16. What is data cleaning?
Removing inaccuracies, duplicates, and inconsistencies in data.
17. Why is data cleaning important?
Ensures accuracy, reliability, and validity of analysis results.
18. What is data wrangling?
Transforming raw data into a usable format for analysis.
19. What is ETL in data analytics?
Extract, Transform, Load: A process for preparing data for analysis.
20. What is data normalization?
Organizing data to reduce redundancy and improve integrity.
21. What is data enrichment?
Enhancing existing data by adding relevant external data sources.
22. What is missing data imputation?
Techniques to handle missing data, such as mean substitution or regression imputation.
23. What is a data dictionary?
A document that describes the structure, content, and format of data.
24. What is data deduplication?
Identifying and removing duplicate records.
25. What is data integrity?
Ensuring data is accurate, consistent, and reliable.
Section 3: Advanced Excel for Accountants
26. What is a pivot table in Excel?
A tool for summarizing and analyzing large datasets.
27. What is conditional formatting in Excel?
A feature that changes cell appearance based on specific criteria.
28. What is the VLOOKUP function in Excel?
A function to search for a value in a column and return data from the same row.
29. What is a macro in Excel?
A script that automates repetitive tasks.
30. What is the purpose of slicers in Excel?
Interactive buttons that filter data in pivot tables or charts.
Here is the continuation of 200 questions and answers for WGU D553: Data Analytics for
Accountants II.
Section 3: Advanced Excel for Accountants (continued)
