Question

    Which of the following best describes the primary

    purpose of a data warehouse in analytics?
    A To store raw, unprocessed data for analysis by data scientists. Correct Answer Incorrect Answer
    B To provide a central repository for integrated data that can be queried and analyzed for decision-making. Correct Answer Incorrect Answer
    C To store transactional data for real-time business operations. Correct Answer Incorrect Answer
    D To manage the flow of data between multiple databases in real-time. Correct Answer Incorrect Answer
    E To optimize and store machine learning models used in production systems. Correct Answer Incorrect Answer

    Solution

    A data warehouse is a specialized system used for storing and managing large amounts of structured data that is used for analysis and reporting. The primary purpose of a data warehouse is to integrate data from multiple sources and provide a centralized repository that can be queried for decision-making. Data from various operational systems is extracted, transformed, and loaded (ETL) into the data warehouse, where it is stored in a format optimized for querying and reporting. This makes it a valuable resource for business intelligence and analytics. • Why this is correct: The key purpose of a data warehouse is to facilitate analysis and decision-making by providing a centralized, integrated data repository. This helps organizations make data-driven decisions based on historical trends and patterns. ________________________________________ Why Other Options Are Incorrect: 1. To store raw, unprocessed data: Data warehouses store processed data that has been transformed to be useful for analysis, not raw, unprocessed data. 2. To store transactional data for real-time business operations: Data warehouses store historical data for analysis rather than real-time transactional data. Operational systems are typically used for real-time processing. 3. To manage the flow of data between multiple databases in real-time: This is the role of a data integration tool or data pipeline, not a data warehouse. 4. To optimize and store machine learning models: Machine learning models are typically stored in model management systems, not in a data warehouse.

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