Enlist the components of a data warehouse.

A data warehouse is a subject-oriented, integrated, time-variant, and non-volatile collection of data designed to support managerial decision-making. Its key components are:

1. Data Sources: External and internal databases, transactional systems, and legacy systems that feed raw data into the warehouse.
2. ETL (Extract, Transform, Load) Process: Extracts data from sources, cleanses and transforms it, and loads it into the warehouse.
3. Data Storage: Centralized repository storing structured, historical, and integrated data in optimized formats (e.g., star schema, snowflake schema).
4. Metadata: Descriptive information about data (e.g., origin, format, meaning, and usage rules) to aid navigation and management.
5. OLAP (Online Analytical Processing) Tools: Enables multidimensional analysis (e.g., slicing, dicing, drilling) for reporting and querying.
6. Data Marts: Subsets of the data warehouse tailored for specific departments or business functions (e.g., sales, finance).
7. Front-End Tools: User interfaces (e.g., dashboards, reporting tools, data mining software) for querying and visualizing data.
8. Data Warehouse Server: Manages storage, retrieval, and processing of data efficiently.
9. Data Warehouse Administration: Ensures security, performance, and maintenance through governance policies and monitoring.