1.
What is the main purpose of the Extract phase in data
warehousing?
A. To clean and transform data
B. To load data into the data warehouse
C. To retrieve data from source systems
D. To aggregate data for analysis
2. What is the main role of a data architect in a data
warehousing project?
A. To manage daily operational tasks
B. To design the logical and physical structure of the data
warehouse
C. To extract data from operational systems
D. To develop user interfaces for data reporting
3. What is the main function of the Load phase in data
warehousing?
A. To cleanse and validate data
B. To aggregate data for reporting
C. To transform data into a new format
D. To move data into the data warehouse
4. Which of the following best describes a star schema?
A. A database schema where the fact table is in the center
connected to multiple dimension tables
B. A schema with multiple fact tables joined by dimensions
C. A complex schema with a large number of foreign keys
D. A type of relational database schema with many-to-many
relationships
5. Extract, Transform, Load refers to:
A. A tool used for creating reports and visualizations
B. A method for extracting data from various sources,
transforming it, and loading it into a data warehouse
C. A process for transferring data between transactional systems
D. A database optimization technique
6. What is a Data Warehouse?
A. A repository of historical data for analysis and reporting
B. A transactional database for day-to-day operations
C. A database designed for online transaction processing
D. A system used for storing large amounts of raw data
7. Which of the following is a key component of data
warehousing?
A. Data mining
B. Online transaction processing
C. Structured Query Language
D. Data aggregation
8. What is the primary purpose of a data warehouse?
A. To support transaction processing
B. To store data for operational systems
C. To support decision-making and analysis
D. To manage daily operational tasks
9. Data warehousing primarily focuses on which type of data
processing?
A. Operational processing
B. Analytical processing
C. Real-time processing
D. Embedded processing
10. Data in a data warehouse is typically:
A. Current and real-time
B. Historical and non-volatile
C. Temporary and frequently updated
D. Dynamic and changing continuously
11. What is a dimension table in a data warehouse?
A. A1 table that contains detailed records of transactions
B. A table that provides descriptive information about the facts in
the fact table
C. A table with real-time operational data
D. A temporary table used for quick lookups
12. Which of the following best describes a snowflake
schema?
A. A simple one-to-one relationship between facts and
dimensions
B. A normalized extension of a star schema with multiple related
dimension tables
C. A schema designed for real-time processing
D. A flat table structure used in data marts
13. What is the main advantage of analytical processing over
transaction processing in data analysis?
A. Faster transaction processing
B. Better analytical capabilities
C. Real-time updates
D. Lower storage costs
14. What is data granularity in a data warehouse?
A. The size of the data stored in the warehouse
B. The level of detail of data stored in the warehouse
C. The frequency of data updates
D. The number of users accessing the data
15. A fact table in a data warehouse stores:
A. Detailed transactional data
B. Metadata
C. Dimensional attributes
D. Aggregate data
16. Which of the following best describes data marts?
A. Small, specialized data warehouses used for departmental
purposes
B. Large, centralized repositories of data for enterprise-wide
analysis
C. Real-time databases for operational systems
D. Unstructured databases used for data mining
17. In a data warehouse, metadata refers to:
A. The actual data stored in the warehouse
B. Data about the data stored in the warehouse
C. Transactional data from operational systems
D. Aggregated historical data
18. What is a surrogate key in a data warehouse?
A. A primary key from an operational system
B. A foreign key in a dimension table
C. A substitute for the natural primary key in dimension tables
D. A key that connects fact and dimension tables
19. Which of the following is NOT an example of a data
transformation process?
A. Data cleansing
B. Data aggregation
C. Data replication
D. Data validation
20. Which of the following systems provides the fastest
response time for complex queries?
A. Analytical processing
B. Transaction processing
C. Data mining
D. Enterprise resource planning
21. The process of improving the performance of a data
warehouse query is called:
A. Data cleansing
B. Data aggregation
C. Query optimization
D. Data normalization
22. What is a typical feature of analytical processing
systems?
A. High write throughput
B. Real-time transaction processing
C. Multidimensional analysis
D. Limited historical data storage
23. Which of the following describes the term “slowly
changing dimension”?
A. A dimension that changes very frequently
B. A dimension that remains static
C. A dimension whose data changes slowly over time
D. A dimension updated in real-time
24. Which of the following is NOT typically a challenge in
data warehousing?
A. Data integration
B. Data consistency
C. Handling of real-time transactions
D. Data scalability
25. Which of the following best describes a factless fact
table?
A. A fact table that contains only foreign keys from dimension
tables without numerical facts
B. A fact table that stores no transactional data
C. A dimension table that stores only descriptive information
D. A fact table that lacks aggregation capabilities
26. The process of reducing data redundancy in a data
warehouse is called:
A. Data cleansing
B. Data transformation
C. Data normalization
D. Data aggregation
27. Which of the following systems is typically used for
managing transactional data?
A. Online analytical processing
B. Data extraction
C. Online transaction processing
D. Business intelligence
28. What is meant by “data latency” in data warehousing?
A. The amount of time it takes to load data into the warehouse
B. The time delay between data capture and data availability for
analysis
C. The time it takes for a query to execute
D. The total time taken by the extraction process
29. What is the primary benefit of using dimensional
modeling in data warehousing?
A. Increased normalization
B. Simplified queries and improved query performance
C. Faster data loading
D. Greater data flexibility
30. What is the difference between operational databases and
data warehouses?
A. Operational databases store historical data, while data
warehouses store real-time data
B. Operational databases are optimized for analysis, while data
warehouses are optimized for transactions
C. Operational databases are used for daily operations, while
data warehouses are used for decision support
D. There is no difference between the two
