This set of Multiple Choice Questions (MCQs) covers important concepts of Data Warehousing, including OLAP, OLTP, ETL, fact tables, dimension tables, star schema, snowflake schema, and data mining fundamentals. Useful for GATE, UGC NET, University Semester Exams, and Database Management System preparation.
Topic: Data Warehousing | Set: 1
Difficulty: Easy to Medium | Total Questions: 15
Data Warehousing MCQs with Answers
Q1. What is a Data Warehouse?
A. A database for transactional processing (OLTP)
B. A subject-oriented, integrated, time-variant, non-volatile collection of data
C. A tool for real-time application development
D. A simple storage folder for text files
View Answer & Explanation
Answer: B
Explanation: A data warehouse is designed to support decision-making rather than day-to-day operations.
Q2. What does OLAP stand for?
A. Online Local Analytical Processing
B. Online Analytical Processing
C. Online Linear Analytical Programming
D. Offline Logical Analytical Processing
View Answer & Explanation
Answer: B
Explanation: OLAP provides multidimensional analytical views of data.
Q3. Which schema uses a central Fact table surrounded by Dimension tables?
A. Star Schema
B. Snowflake Schema
C. Galaxy Schema
D. Normalized Schema
View Answer & Explanation
Answer: A
Explanation: The star schema is the simplest form of a data warehouse schema.
Q4. “Time-variant” in Data Warehousing means:
A. Data is updated every second
B. Data is stored in chronological order and captures history
C. Data is deleted periodically
D. Data is only for current time
View Answer & Explanation
Answer: B
Explanation: Time-variance allows historical analysis by keeping records over long periods.
Q5. Which process involves converting data from source formats to destination formats?
A. ETL (Extract, Transform, Load)
B. Backup
C. Compression
D. Encryption
View Answer & Explanation
Answer: A
Explanation: ETL is the core process of moving data into a warehouse.
Q6. What is a “Fact Table”?
A. A table containing descriptive attributes of an entity
B. A table containing quantitative data (measures) for analysis
C. A table containing metadata only
D. A table containing login logs
View Answer & Explanation
Answer: B
Explanation: Fact tables contain numerical measures like sales, revenue, or counts.
Q7. A Snowflake schema is characterized by:
A. Fully denormalized dimensions
B. Normalized dimension tables
C. No dimension tables
D. A single table
View Answer & Explanation
Answer: B
Explanation: Snowflake schemas normalize dimension tables to reduce redundancy.
Q8. Metadata is:
A. Data about data
B. Raw data from the source
C. Archived data
D. Corrupted data
View Answer & Explanation
Answer: A
Explanation: Metadata describes the structure and context of the data warehouse.
Q9. Which of these is an example of an OLTP system?
A. Data Warehouse
B. Retail Point-of-Sale System
C. Reporting Dashboard
D. OLAP Cube
View Answer & Explanation
Answer: B
Explanation: OLTP systems manage current, day-to-day transactions.
Q10. What is Data Mining?
A. Extracting large amounts of coal
B. The process of discovering patterns and knowledge from large datasets
C. The process of deleting old database logs
D. Formatting data for storage
View Answer & Explanation
Answer: B
Explanation: Data mining uses statistical and AI techniques to find hidden insights.
Q11. “Drill-down” in OLAP refers to:
A. Moving from general data to more specific, detailed data
B. Moving from specific to general
C. Deleting data
D. Changing data types
View Answer & Explanation
Answer: A
Explanation: Drill-down increases the level of detail (e.g., Year -> Month -> Day).
Q12. What is a Data Mart?
A. A giant data warehouse for a whole corporation
B. A subset of a data warehouse focused on a specific department
C. A backup of the production database
D. A data mining algorithm
View Answer & Explanation
Answer: B
Explanation: Data marts are smaller, departmental versions of a warehouse.
Q13. Non-volatile means:
A. Data changes constantly
B. Data, once loaded, does not change or get deleted
C. Data is lost on reboot
D. Data is encrypted
View Answer & Explanation
Answer: B
Explanation: Non-volatile implies historical integrity; you don’t update/delete historical warehouse records.
Q14. Slicing in OLAP means:
A. Picking one dimension to create a 2D view
B. Picking multiple dimensions
C. Combining two tables
D. Filtering rows
View Answer & Explanation
Answer: A
Explanation: Slicing selects one dimension to reduce the cube’s dimensionality.
Q15. What is an attribute?
A. A column in a dimension table
B. A row in a fact table
C. An entire database
D. A software update
View Answer & Explanation
Answer: A
Explanation: Attributes are descriptive characteristics (e.g., ‘Color’, ‘Brand’).
Conclusion
These Data Warehousing MCQ questions covered important concepts such as OLAP, OLTP, ETL, fact tables, dimension tables, star schema, snowflake schema, and data mining fundamentals.
Practicing these questions is useful for Database Management Systems, Big Data Technology, GATE CS, UGC NET, and university semester examinations.
For detailed understanding of theory and concepts, refer to Data Warehousing – Concepts.