Data Warehousing and Data Warehouse Concepts
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Data Warehousing and Data Warehouse Concepts

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Questions and Answers

What is a major challenge of using data lakes?

  • Requires predefined schemas
  • Limited scalability
  • High implementation costs
  • Data quality and governance issues (correct)
  • Which of the following is a feature of cloud data warehousing?

  • Requirement for on-premises infrastructure
  • Fixed hardware requirements
  • Limited data storage capabilities
  • Dynamic scaling based on workload (correct)
  • What is an advantage of a data lakehouse compared to traditional data warehouses?

  • It allows for ACID transactions (correct)
  • It eliminates data governance needs
  • It stores only structured data
  • It requires specialized hardware
  • Which of these is NOT a characteristic of traditional data warehousing architecture?

    <p>Support for both structured and unstructured data</p> Signup and view all the answers

    What benefit does a data lake provide over traditional data warehouses?

    <p>Flexibility in data formats</p> Signup and view all the answers

    What is a primary advantage of using data marts?

    <p>They provide structured, historical data for specific business areas.</p> Signup and view all the answers

    Which of the following represents a challenge associated with data lakes?

    <p>Difficulty in managing diverse data formats effectively.</p> Signup and view all the answers

    What is a key feature of cloud data warehousing?

    <p>Pay-as-you-go pricing models reducing overall costs.</p> Signup and view all the answers

    Which aspect distinguishes federated data warehouses from traditional data warehouses?

    <p>They create a virtual layer to access disparate databases in real time.</p> Signup and view all the answers

    What is a significant benefit of data lakehouses?

    <p>They combine features of both data lakes and data warehouses.</p> Signup and view all the answers

    Study Notes

    Data Warehousing

    • Serves as a central repository for reporting and data analysis.
    • Integrates data from multiple sources.
    • Stores current and historical data.
    • Used for creating analytical reports for business intelligence activities.
    • Primary goal is to support decision making.

    Data Warehouse

    • A large, centralized repository that integrates data from various sources.
    • Designed for complex queries, analytics, and reporting processes.
    • Contains vast amounts of historical data, facilitating trend analysis, forecasting, and business intelligence.
    • Key characteristics include:
      • Subject-oriented: Organizes data around key business subjects, making it easier to access relevant information.
      • Integrated: Combines data from different sources into a coherent format, ensuring consistency.
      • Time-variant: Stores historical data to provide a time-based perspective for analysis.
      • Non-volatile: Once data enters the warehouse, it is not frequently modified or deleted, preserving data integrity.

    Data Marts

    • A smaller, more focused subset of a data warehouse.
    • Caters to the specific needs of a particular department or business unit.
    • Designed for more specialized analytical processing.
    • Types:
      • Dependent Data Marts: Sourced directly from a centralized data warehouse.
      • Independent Data Marts: Created without relying on a central data warehouse, gathering data from operational systems or external sources.
    • Advantages:
      • Quicker access to relevant data for a specific department.
      • Easier and faster implementation compared to full-scale data warehouses.
    • Disadvantages:
      • Potential for data inconsistency if not integrated with a central warehouse.
      • Limited scope of data, making cross-departmental analysis more challenging.

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    Related Documents

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    Description

    This quiz covers the essential concepts of Data Warehousing and the characteristics of a Data Warehouse. Learn how data is integrated from multiple sources, stored for analysis, and utilized for business intelligence activities. Test your understanding of how these systems support decision-making processes.

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