Data Warehousing Engineering

Häftad, Engelska, 1999

618 kr

Beställningsvara. Skickas inom 3-6 vardagar. Fri frakt över 249 kr.

Beskrivning

This text on data warehouse engineering takes readers from the planning and modelling stages right through to the implementation. It includes chapters on how to convert data from a legacy system to a modern data warehouse.

Produktinformation

Utgivningsdatum:1999-08-26
Mått:190 x 235 x 29 mm
Vikt:952 g
Format:Häftad
Språk:Engelska
Serie:Enterprise Computing S.
Antal sidor:529
Förlag:McGraw-Hill Education - Europe
ISBN:9780079137050

Utforska kategorier

Databaser inom Data och IT

Innehållsförteckning

Part 1 Data warehousing concepts (defining business needs): data, warehouse and engineering concepts; strategic business planning; data mapping - a window into the enterprise; strategic modelling - a map for the future; decision early warning - a common need. Part 2 Data quality and legacy systems: the importance of legacy system metadata; defining required legacy system metadata requirements; deriving legacy system metadata; determining relevant data quality attributes; data quality engineering. Part 3 Engineering the data warehouse: moving the past into the future; data warehousing as a reengineering technology; implementing organizational data quality initiatives; continuous data quality engineering; future data warehouse directions.

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Data Warehousing Engineering

AvClive Finklestein,Peter Aiken

Häftad, Engelska, 1999

Del i serien Enterprise Computing S.

618 kr

Beställningsvara. Skickas inom 3-6 vardagar. Fri frakt över 249 kr.

Beskrivning

Produktinformation

Utgivningsdatum:1999-08-26
Mått:190 x 235 x 29 mm
Vikt:952 g
Format:Häftad
Språk:Engelska
Serie:Enterprise Computing S.
Antal sidor:529
Förlag:McGraw-Hill Education - Europe
ISBN:9780079137050

Utforska kategorier

Databaser inom Data och IT

Innehållsförteckning

Part 1 Data warehousing concepts (defining business needs): data, warehouse and engineering concepts; strategic business planning; data mapping - a window into the enterprise; strategic modelling - a map for the future; decision early warning - a common need. Part 2 Data quality and legacy systems: the importance of legacy system metadata; defining required legacy system metadata requirements; deriving legacy system metadata; determining relevant data quality attributes; data quality engineering. Part 3 Engineering the data warehouse: moving the past into the future; data warehousing as a reengineering technology; implementing organizational data quality initiatives; continuous data quality engineering; future data warehouse directions.