Business Intelligence, Analytics, Data Science & AI (2025) | APLUS Latest Edition Guide

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Business Intelligence, Analytics, Data
Science, and AI (latest Edition)

1. What is the primary goal of Business Intelligence
(BI)?

 A. To store data in data lakes
 B. To create new programming languages
 C. To support better decision-making
 D. To eliminate human decision-making
Rationale: BI helps convert raw data into actionable
insights to improve business decisions.


2. In the BI process, which of the following is typically
the first step?

 A. Data visualization
 B. Data warehouse querying
 C. Data collection
 D. Report generation
Rationale: Data must be collected before it can be
processed or analyzed.


3. Which of the following best describes the concept of
a data warehouse?

 A. A cloud-based data archive
 B. A collection of unstructured real-time data
 C. A centralized repository for integrated data from
multiple sources

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 D. A software package for creating dashboards
Rationale: A data warehouse stores consolidated,
structured data for querying and analysis.


4. What are the three main types of analytics used in BI?

 A. Descriptive, Diagnostic, Predictive
 B. Historical, Real-time, Future-based
 C. Manual, Automated, Hybrid
 D. Business, Operational, Strategic
Rationale: These cover what happened, why it
happened, and what might happen.


5. What is the function of ETL in the context of data
warehousing?

 A. Extract, Transform, Load
 B. Evaluate, Track, Learn
 C. Execute, Test, Log
 D. Extract, Tabulate, Link
Rationale: ETL is used to prepare data for analysis by
extracting, transforming, and loading it into a
warehouse.


6. Which of the following is an example of unstructured
data?

 A. Excel spreadsheets
 B. SQL database tables
 C. Social media posts

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 D. Sales transaction logs
Rationale: Social media posts do not have a
predefined data model, making them unstructured.


7. Which technique is commonly used for predictive
analytics?

 A. OLAP
 B. Regression analysis
 C. Reporting tools
 D. Descriptive statistics
Rationale: Regression helps predict future outcomes
based on historical data.


8. What does OLAP stand for in BI systems?

 A. Online Link and Access Processing
 B. Online Analytical Processing
 C. Operational Layer for Analytics Programming
 D. Open Logic Algorithm Protocol
Rationale: OLAP allows users to analyze data across
multiple dimensions interactively.


9. Which type of AI mimics human thinking to solve
problems?

 A. Basic automation
 B. Cognitive computing
 C. Data mining
 D. Reporting tools
Rationale: Cognitive computing uses AI to simulate
human reasoning and decision-making.

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10. In the context of data mining, what is classification
used for?

 A. Grouping customers without labels
 B. Assigning items to predefined categories
 C. Compressing large datasets
 D. Extracting new data from APIs
Rationale: Classification assigns new data points to
existing categories based on training data.



11. What is a key advantage of cloud-based BI
solutions?

 A. They require expensive hardware
 B. They are scalable and cost-effective
 C. They reduce internet usage
 D. They eliminate the need for data
Rationale: Cloud BI platforms allow organizations to
scale easily and avoid infrastructure costs.


12. Which of the following is NOT typically part of a BI
architecture?

 A. Data sources
 B. ETL tools
 C. Video rendering software
 D. Data marts
Rationale: Video rendering tools are not used in BI
architectures.