WGU D491 Study Guide (Updated 2026/2027 Syllabus)
100+ Answered Questions
Introduction to Data Analytics
1. What is the primary goal of data analytics?
ANSWER ✓ The primary goal of data analytics is to extract meaningful insights from raw
data to support decision-making, identify trends, and solve business problems.
2. Define structured data.
ANSWER ✓ Structured data is organized in a predefined format, often in tables with
rows and columns, making it easily searchable and analyzable (e.g., SQL databases,
spreadsheets).
3. Define unstructured data.
ANSWER ✓ Unstructured data lacks a predefined format and includes text, images,
audio, and social media posts, requiring advanced techniques for processing and
analysis.
4. What are the four main types of data analytics?
ANSWER ✓ Descriptive (what happened), Diagnostic (why it happened), Predictive (what
will happen), and Prescriptive (what should be done).
5. How does business intelligence differ from data analytics?
ANSWER ✓ Business intelligence focuses on historical data and reporting for operational
insights, while data analytics uses statistical and computational methods to predict
future trends and prescribe actions.
Data Collection & Management
6. What is data wrangling?
ANSWER ✓ Data wrangling involves cleaning, transforming, and organizing raw data
into a usable format for analysis.
, 7. Explain ETL (Extract, Transform, Load).
ANSWER ✓ ETL is a process that extracts data from multiple sources, transforms it to fit
operational needs, and loads it into a data warehouse for analysis.
8. What is a data warehouse?
ANSWER ✓ A data warehouse is a centralized repository for storing integrated, historical
data from multiple sources, optimized for querying and analysis.
9. Define data mart.
ANSWER ✓ A data mart is a subset of a data warehouse, designed for a specific business
line or department (e.g., sales, finance).
10. What is the difference between OLTP and OLAP?
ANSWER ✓ OLTP (Online Transaction Processing) handles real-time transactional
operations, while OLAP (Online Analytical Processing) supports complex queries and
data analysis.
11. What is data governance?
ANSWER ✓ Data governance refers to the overall management of data availability,
usability, integrity, and security within an organization.
12. Explain data stewardship.
ANSWER ✓ Data stewardship involves overseeing data assets to ensure they are
managed properly and comply with governance policies.
13. What is a data dictionary?
ANSWER ✓ A data dictionary is a centralized repository of metadata that describes the
structure, meaning, and relationships of data elements.
14. Define data quality and list three dimensions.
ANSWER ✓ Data quality ensures data is accurate, consistent, and reliable. Dimensions
include accuracy, completeness, timeliness, consistency, and validity.
15. What is data profiling?
ANSWER ✓ Data profiling is the process of examining data to understand its structure,
content, and quality.
Data Analysis Techniques
100+ Answered Questions
Introduction to Data Analytics
1. What is the primary goal of data analytics?
ANSWER ✓ The primary goal of data analytics is to extract meaningful insights from raw
data to support decision-making, identify trends, and solve business problems.
2. Define structured data.
ANSWER ✓ Structured data is organized in a predefined format, often in tables with
rows and columns, making it easily searchable and analyzable (e.g., SQL databases,
spreadsheets).
3. Define unstructured data.
ANSWER ✓ Unstructured data lacks a predefined format and includes text, images,
audio, and social media posts, requiring advanced techniques for processing and
analysis.
4. What are the four main types of data analytics?
ANSWER ✓ Descriptive (what happened), Diagnostic (why it happened), Predictive (what
will happen), and Prescriptive (what should be done).
5. How does business intelligence differ from data analytics?
ANSWER ✓ Business intelligence focuses on historical data and reporting for operational
insights, while data analytics uses statistical and computational methods to predict
future trends and prescribe actions.
Data Collection & Management
6. What is data wrangling?
ANSWER ✓ Data wrangling involves cleaning, transforming, and organizing raw data
into a usable format for analysis.
, 7. Explain ETL (Extract, Transform, Load).
ANSWER ✓ ETL is a process that extracts data from multiple sources, transforms it to fit
operational needs, and loads it into a data warehouse for analysis.
8. What is a data warehouse?
ANSWER ✓ A data warehouse is a centralized repository for storing integrated, historical
data from multiple sources, optimized for querying and analysis.
9. Define data mart.
ANSWER ✓ A data mart is a subset of a data warehouse, designed for a specific business
line or department (e.g., sales, finance).
10. What is the difference between OLTP and OLAP?
ANSWER ✓ OLTP (Online Transaction Processing) handles real-time transactional
operations, while OLAP (Online Analytical Processing) supports complex queries and
data analysis.
11. What is data governance?
ANSWER ✓ Data governance refers to the overall management of data availability,
usability, integrity, and security within an organization.
12. Explain data stewardship.
ANSWER ✓ Data stewardship involves overseeing data assets to ensure they are
managed properly and comply with governance policies.
13. What is a data dictionary?
ANSWER ✓ A data dictionary is a centralized repository of metadata that describes the
structure, meaning, and relationships of data elements.
14. Define data quality and list three dimensions.
ANSWER ✓ Data quality ensures data is accurate, consistent, and reliable. Dimensions
include accuracy, completeness, timeliness, consistency, and validity.
15. What is data profiling?
ANSWER ✓ Data profiling is the process of examining data to understand its structure,
content, and quality.
Data Analysis Techniques
