AIN3701 EXAM PACK STUDY GUIDE 2025/2026
ACCURATE QUESTIONS BANK AND CORRECT
ANSWERS WITH RATIONALES || 100%
GUARANTEED PASS <UPDATED VERSION>
AIN3701 EXAM PACK STUDY GUIDE 2025/2026
Accurate Questions Bank and Correct Answers with Rationales
Section 1: Introduction to Business Intelligence (BI) and Data Analytics
1. What is the primary goal of Business Intelligence (BI)?
• Answer: To support better business decision-making through data-driven insights and
analysis.
• Rationale: BI transforms raw data into meaningful information, providing a historical,
current, and predictive view of business operations, which is foundational for strategic
planning.
2. Differentiate between Business Intelligence and Data Analytics.
• Answer: BI is primarily descriptive, focusing on what happened in the past and present
(reporting, dashboards). Data Analytics is more predictive and prescriptive, using
, statistical and quantitative analysis to understand why it happened and what will happen
next.
• Rationale: While often used interchangeably, BI is a subset of the broader data analytics
field, with the latter encompassing advanced techniques like forecasting and
optimization.
3. Which component of a BI system is responsible for the storage of processed and
structured data ready for analysis?
• Answer: The Data Warehouse or Data Mart.
• Rationale: The data warehouse is the central repository that integrates data from various
sources, transforming it into a consistent format for querying and analysis.
4. The process of extracting data from source systems, transforming it into a clean and
consistent format, and loading it into a data warehouse is known as:
• Answer: ETL (Extract, Transform, Load).
• Rationale: ETL is the core process that populates a data warehouse, ensuring data quality
and usability.
5. A dashboard that shows Key Performance Indicators (KPIs) like current month's sales
and year-to-date revenue is an example of what type of analytics?
• Answer: Descriptive Analytics.
• Rationale: It describes what has already happened, providing a summary of historical
data.
, Section 2: Data Warehousing and ETL
6. What is the main difference between a Data Warehouse and a Data Mart?
• Answer: A Data Warehouse is a central, enterprise-wide repository, while a Data Mart is
a subset of a data warehouse, designed for a specific business line or department (e.g.,
finance, sales).
• Rationale: Data marts are smaller, more focused, and often built from a data warehouse
to serve departmental needs more efficiently.
7. The Kimball methodology for data warehousing is best known for its use of:
• Answer: Dimensional Modeling (Star Schemas).
• Rationale: The Kimball approach advocates for a bottom-up development starting with
business processes, modeled using fact and dimension tables in a star schema for user
understandability and query performance.
8. In a Star Schema, what type of table contains the quantitative metrics (e.g., sales
amount, quantity sold) of a business process?
• Answer: Fact Table.
• Rationale: Fact tables are the center of the star schema and hold the measurable,
quantitative data about business operations.
9. A "Product" table, containing attributes like ProductID, ProductName, and Category, is
an example of what in a dimensional model?
ACCURATE QUESTIONS BANK AND CORRECT
ANSWERS WITH RATIONALES || 100%
GUARANTEED PASS <UPDATED VERSION>
AIN3701 EXAM PACK STUDY GUIDE 2025/2026
Accurate Questions Bank and Correct Answers with Rationales
Section 1: Introduction to Business Intelligence (BI) and Data Analytics
1. What is the primary goal of Business Intelligence (BI)?
• Answer: To support better business decision-making through data-driven insights and
analysis.
• Rationale: BI transforms raw data into meaningful information, providing a historical,
current, and predictive view of business operations, which is foundational for strategic
planning.
2. Differentiate between Business Intelligence and Data Analytics.
• Answer: BI is primarily descriptive, focusing on what happened in the past and present
(reporting, dashboards). Data Analytics is more predictive and prescriptive, using
, statistical and quantitative analysis to understand why it happened and what will happen
next.
• Rationale: While often used interchangeably, BI is a subset of the broader data analytics
field, with the latter encompassing advanced techniques like forecasting and
optimization.
3. Which component of a BI system is responsible for the storage of processed and
structured data ready for analysis?
• Answer: The Data Warehouse or Data Mart.
• Rationale: The data warehouse is the central repository that integrates data from various
sources, transforming it into a consistent format for querying and analysis.
4. The process of extracting data from source systems, transforming it into a clean and
consistent format, and loading it into a data warehouse is known as:
• Answer: ETL (Extract, Transform, Load).
• Rationale: ETL is the core process that populates a data warehouse, ensuring data quality
and usability.
5. A dashboard that shows Key Performance Indicators (KPIs) like current month's sales
and year-to-date revenue is an example of what type of analytics?
• Answer: Descriptive Analytics.
• Rationale: It describes what has already happened, providing a summary of historical
data.
, Section 2: Data Warehousing and ETL
6. What is the main difference between a Data Warehouse and a Data Mart?
• Answer: A Data Warehouse is a central, enterprise-wide repository, while a Data Mart is
a subset of a data warehouse, designed for a specific business line or department (e.g.,
finance, sales).
• Rationale: Data marts are smaller, more focused, and often built from a data warehouse
to serve departmental needs more efficiently.
7. The Kimball methodology for data warehousing is best known for its use of:
• Answer: Dimensional Modeling (Star Schemas).
• Rationale: The Kimball approach advocates for a bottom-up development starting with
business processes, modeled using fact and dimension tables in a star schema for user
understandability and query performance.
8. In a Star Schema, what type of table contains the quantitative metrics (e.g., sales
amount, quantity sold) of a business process?
• Answer: Fact Table.
• Rationale: Fact tables are the center of the star schema and hold the measurable,
quantitative data about business operations.
9. A "Product" table, containing attributes like ProductID, ProductName, and Category, is
an example of what in a dimensional model?
