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What Is a Data Warehouse?

By Michelle Knight on
data warehouse

A data warehouse is a centralized repository that stores and provides decision-support data and aids workers engaged in reporting, query, and analysis. Data warehouses represent architected data schemas that make it easy to find relevant data consistently and research details in a stable environment.

Data sources, including data lakes, can pipe data to a data warehouse. Data warehouse integration happens through ETL  (extract, transform, and load) processes. ETL algorithms copy, format, and upload the data for ready use in data warehouses.

Data warehouses provide insight into operational processes and open new possibilities to leverage data towards making decisions and creating organizational value.

Other Definitions of a Data Warehouse Include:

  • A “storage architecture designed to hold data extracted from transaction systems, operational data stores and external sources.” (Gartner)
  • “Provides clearly defined communications, for a known aggregate set of data, to a well-defined user set, like a travel itinerary.” (Michelle Knight)
  • “A tool that is: (Kelle O’Neal and John Ladley)
    • Structured, processed
    • Schema-on-write
    • Expensive for large data volumes
    • A fixed configuration
    • Mature
    • Made for business pros.”
  • A “stable, read only database that combines information from separate systems into one easy-to-access location.” (MIT)
  • “A place like a central distribution and storage warehouse, where individual data marts all come together to reside.” ( Forbes)

Data warehouse Use Cases Include:

Businesses Use Data Warehouses to:

  • Support DataOps, a methodology focused on improving data flow
  • Ensure compliance with requirements
  • Back up business intelligence (BI) activities
  • Comply with audits and regulations
  • Gain insights about the organization, its customers, and its products

Image used under license from Shutterstock.com

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