Methoden vergleichen

	Data Warehousing	ETL Process	OLAP-Würfel-Design
Fachgebiet	Wirtschaftsinformatik	Wirtschaftsinformatik	Wirtschaftsinformatik
Familie	Process / pipeline	Process / pipeline	Process / pipeline
Entstehungsjahr	1992	1996	1993
Urheber	William H. Inmon and Ralph Kimball	Ralph Kimball and data warehouse pioneers	E. F. Codd and colleagues (Arbor Software)
Typ	Data system architecture	Data integration methodology	Analytical data structure design
Wegweisende Quelle	Inmon, W. H. (1992). Building the Data Warehouse. New York: QED Technical Publishing.	Kimball, R. (1996). The Data Warehouse Toolkit: Practical Techniques for Building Dimensional Data Warehouses. New York: John Wiley & Sons.	Codd, E. F., Codd, S. B., & Salley, C. T. (1993). Providing OLAP to user-analysts: An IT mandate. Arbor Software.
Aliasnamen	warehouse, DW design	ETL, data integration	OLAP, multidimensional cubes
Verwandt	2	1	1
Zusammenfassung	Data warehousing is an approach to designing integrated repositories of historical business data optimized for analysis and reporting. Pioneered by William Inmon and Ralph Kimball in the early 1990s, data warehouses consolidate data from diverse operational sources into a centralized, time-stamped, non-volatile store supporting complex queries across multiple dimensions.	The Extract-Transform-Load (ETL) process is a systematic approach to moving data from source systems into a target repository. Formalized in the context of data warehousing, ETL pipelines extract data from diverse operational sources, apply business rules and data quality checks, and load the results into data warehouses and analytical systems.	OLAP (Online Analytical Processing) cube design is the practice of structuring multidimensional data for interactive analysis. Formalized by Codd and colleagues in 1993, OLAP cubes organize facts (measurements) along multiple dimensions (attributes) enabling rapid pivoting, drilling, and aggregation for business analysis.