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DW characteristics vs operational database

Short answer

A data warehouse is subject-oriented, integrated, time-variant, non-volatile, large-volume, decision-support oriented. Unlike operational databases, it stores historical summarized and detailed data, uses denormalized star schemas, supports complex ad hoc queries, and is refreshed periodically rather than updated transaction by transaction.

Explain the characteristics of a Data Warehouse. How is an operational database different from a Data Warehouse?

A data warehouse is a subject-oriented, integrated, time-variant and non-volatile collection of data used for decision making.

Characteristics

  • Subject-oriented: organised around major subjects such as customer, product, sales, not around day-to-day operations.
  • Integrated: data from many sources is made consistent in naming, units, formats and encoding.
  • Time-variant: data is kept as historical snapshots (5-10 years); every record has a time element.
  • Non-volatile: data is loaded and read, but not updated or deleted in place; only refreshed periodically.
  • Large volume: stores years of detailed and summarised data, in GB to TB.
  • Decision-support oriented: built for queries and analysis, not transactions.

Operational database vs data warehouse

PointOperational database (OLTP)Data warehouse
PurposeDay-to-day transactionsAnalysis and decision support
DataCurrent, detailedHistorical, summarised and detailed
OrientationApplication-orientedSubject-oriented
UpdateFrequent insert/update/deletePeriodic bulk load, read-mostly
DesignNormalised (ER model)Denormalised (star/snowflake)
QueryShort, simple, predefinedComplex, ad hoc, aggregate
UsersClerks, DBAs (thousands)Managers, analysts (few)
SizeMB to GBGB to TB

✓ Answer checked by Claude Opus 5.5 (high effort)

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