WGU D514: Data Analytics & Visualization - Study Guide
This guide is organized by major module/concept area to mirror the likely structure of
your course.
Module 1: Foundations of Data & The Data Lifecycle
1. What is the primary goal of data analytics?
ANSWER ✓ To discover, interpret, and communicate meaningful patterns and insights
from data to inform decision-making, drive strategy, and solve complex problems.
2. Define "Data" in the context of analytics.
ANSWER ✓ Raw, unprocessed facts and figures without context. (e.g., 42, 72, 101).
3. Define "Information."
ANSWER ✓ Data that has been processed, organized, or structured to provide context
and meaning. (e.g., A temperature reading of 42°F, a score of 72%, a heart rate of 101
BPM).
4. Define "Knowledge."
ANSWER ✓ The application of information to a specific situation or problem, enabling
action. (e.g., Knowing that a temperature of 42°F requires wearing a coat).
5. What are the four main types of data analytics?
ANSWER ✓
1. Descriptive: What happened? (Reports, Dashboards)
2. Diagnostic: Why did it happen? (Drill-down, Root Cause Analysis)
3. Predictive: What is likely to happen? (Forecasting, Modeling)
4. Prescriptive: What should we do about it? (Optimization, Recommendation)
6. Describe the Data Lifecycle (or Data Processing Cycle).
ANSWER ✓ The sequence of stages that data goes through from its initial generation to
its final archival or deletion. Common stages: Plan/Collect -> Prepare/Process ->
Analyze -> Act/Share -> Archive.
, 7. What is the difference between Data Warehouses and Data Lakes?
ANSWER ✓ A Data Warehouse stores structured, processed data for a specific purpose
(schema-on-write). A Data Lake stores vast amounts of raw data in its native format
(structured, semi-structured, unstructured) until it is needed (schema-on-read).
8. What is ETL?
ANSWER ✓ Extract, Transform, Load. The process of pulling data from source systems,
cleaning and transforming it into a usable format, and loading it into a target database
or data warehouse.
9. What is the primary purpose of a Star Schema in data warehousing?
ANSWER ✓ To optimize data retrieval for analytical queries by structuring data into a
central fact table (containing measures/metrics) surrounded by dimension tables
(containing descriptive attributes).
10. What is a fact table?
ANSWER ✓ The central table in a star schema that contains quantitative measurements
(facts) about a business process (e.g., sales amount, quantity sold).
11. What is a dimension table?
ANSWER ✓ A table in a star schema that contains descriptive attributes related to the
facts (e.g., time, product, customer, location).
Module 2: Data Management, Governance, and Quality
12. What is Data Governance?
ANSWER ✓ The overall management of the availability, usability, integrity, and security
of data in an organization. It involves policies, standards, and processes.
13. What is the difference between Data Integrity and Data Quality?
This guide is organized by major module/concept area to mirror the likely structure of
your course.
Module 1: Foundations of Data & The Data Lifecycle
1. What is the primary goal of data analytics?
ANSWER ✓ To discover, interpret, and communicate meaningful patterns and insights
from data to inform decision-making, drive strategy, and solve complex problems.
2. Define "Data" in the context of analytics.
ANSWER ✓ Raw, unprocessed facts and figures without context. (e.g., 42, 72, 101).
3. Define "Information."
ANSWER ✓ Data that has been processed, organized, or structured to provide context
and meaning. (e.g., A temperature reading of 42°F, a score of 72%, a heart rate of 101
BPM).
4. Define "Knowledge."
ANSWER ✓ The application of information to a specific situation or problem, enabling
action. (e.g., Knowing that a temperature of 42°F requires wearing a coat).
5. What are the four main types of data analytics?
ANSWER ✓
1. Descriptive: What happened? (Reports, Dashboards)
2. Diagnostic: Why did it happen? (Drill-down, Root Cause Analysis)
3. Predictive: What is likely to happen? (Forecasting, Modeling)
4. Prescriptive: What should we do about it? (Optimization, Recommendation)
6. Describe the Data Lifecycle (or Data Processing Cycle).
ANSWER ✓ The sequence of stages that data goes through from its initial generation to
its final archival or deletion. Common stages: Plan/Collect -> Prepare/Process ->
Analyze -> Act/Share -> Archive.
, 7. What is the difference between Data Warehouses and Data Lakes?
ANSWER ✓ A Data Warehouse stores structured, processed data for a specific purpose
(schema-on-write). A Data Lake stores vast amounts of raw data in its native format
(structured, semi-structured, unstructured) until it is needed (schema-on-read).
8. What is ETL?
ANSWER ✓ Extract, Transform, Load. The process of pulling data from source systems,
cleaning and transforming it into a usable format, and loading it into a target database
or data warehouse.
9. What is the primary purpose of a Star Schema in data warehousing?
ANSWER ✓ To optimize data retrieval for analytical queries by structuring data into a
central fact table (containing measures/metrics) surrounded by dimension tables
(containing descriptive attributes).
10. What is a fact table?
ANSWER ✓ The central table in a star schema that contains quantitative measurements
(facts) about a business process (e.g., sales amount, quantity sold).
11. What is a dimension table?
ANSWER ✓ A table in a star schema that contains descriptive attributes related to the
facts (e.g., time, product, customer, location).
Module 2: Data Management, Governance, and Quality
12. What is Data Governance?
ANSWER ✓ The overall management of the availability, usability, integrity, and security
of data in an organization. It involves policies, standards, and processes.
13. What is the difference between Data Integrity and Data Quality?
