PostgreSQL, often referred to as Postgres, is a powerful open-source relational database management system (RDBMS) known for its scalability, robustness, and extensibility. It offers advanced features like ACID compliance, support for complex data types, and support for both SQL and NoSQL data. PostgreSQL is highly regarded for its performance, security, and reliability, making it a popular choice for applications ranging from small startups to large enterprises. Its active developer community continuously enhances and maintains the software. PostgreSQL is an excellent choice for data storage, analysis, and management in various domains, including web applications, data warehousing, and geospatial applications.
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Practice Test
151. What is the primary purpose of a data warehouse in the context of PostgreSQL?
A. To store and consolidate historical data for analysis and reporting
B. To create new databases
C. To optimize query performance
D. To manage user roles
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Answer: To store and consolidate historical data for analysis and reporting
152. What does the term "ETL" stand for in data warehousing with PostgreSQL?
A. Extract, Transform, Load
B. Enhance, Transfer, Link
C. Edit, Test, Learn
D. Execute, Transmit, Log
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Answer: Extract, Transform, Load
153. Which PostgreSQL feature is often used for handling large volumes of data in data warehousing?
A. Partitioning
B. Indexing
C. Row-level security
D. Triggers
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Answer: Partitioning
154. What is a "star schema" in the context of data warehousing with PostgreSQL?
A. A schema design where fact tables are connected to dimension tables
B. A schema for encrypting data at rest
C. A schema for creating new databases
D. A schema for optimizing query performance
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Answer: A schema design where fact tables are connected to dimension tables
155. What does the "fact table" represent in a star schema of a data warehouse?
A. It contains measures and numeric data for analysis
B. It stores user access logs
C. It creates new databases
D. It enforces strong password requirements
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Answer: It contains measures and numeric data for analysis
156. What is the purpose of "OLAP" in data warehousing with PostgreSQL?
A. Online Analytical Processing (OLAP) is used for complex, interactive analysis of data in a data warehouse
B. To create physical backups of the data warehouse
C. To manage database connections
D. To encrypt data during transmission
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Answer: Online Analytical Processing (OLAP) is used for complex, interactive analysis of data in a data warehouse
157. What is the role of "cubes" in multidimensional analysis in data warehousing with PostgreSQL?
A. Cubes provide a structured way to aggregate and explore data for analytical purposes
B. Cubes are used for storing binary data
C. Cubes manage database indexes
D. Cubes optimize query performance
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Answer: Cubes provide a structured way to aggregate and explore data for analytical purposes
158. What is "slowly changing dimension" (SCD) in data warehousing with PostgreSQL?
A. It refers to handling changes in data over time, especially in dimension tables
B. It is used to create new databases
C. It optimizes query performance
D. It enforces strong password requirements
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Answer: It refers to handling changes in data over time, especially in dimension tables
159. Which PostgreSQL extension is commonly used for data warehousing to manage large datasets?
A. "pgCube"
B. "pgETL"
C. "pgPartitions"
D. "pgBouncer"
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Answer: "pgCube"
160. In data warehousing, what does "denormalization" refer to?
A. Combining data from multiple normalized tables into a single table for performance
B. Creating additional databases
C. Encrypting data during transmission
D. Managing user roles
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Answer: Combining data from multiple normalized tables into a single table for performance
