Comparative study of data warehouses modeling approaches: Inmon, Kimball and Data Vault | IEEE Conference Publication | IEEE Xplore

Comparative study of data warehouses modeling approaches: Inmon, Kimball and Data Vault


Abstract:

BI (Business Intelligence) is an important discipline for companies and the challenges it faces are strategic. A central concept in BI is the data warehouse, which is a s...Show More

Abstract:

BI (Business Intelligence) is an important discipline for companies and the challenges it faces are strategic. A central concept in BI is the data warehouse, which is a set of consolidated data from heterogeneous sources (usually databases in 3NF). To model the data warehouse, the Inmon and Kimball approaches are the most used. Both solutions monopolize the BI market However, a third modeling approach called “Data Vault” of its creator Linstedt, is gaining ground from year to year. It allows building a data warehouse of raw (unprocessed) data from heterogeneous sources. The purpose of this paper is to present a comparative study of the three precedent approaches. First, we study each approach separately and then we draw a comparison between them. Finally, we include recommendations for selecting the best approach before concluding this paper.
Date of Conference: 15-18 November 2016
Date Added to IEEE Xplore: 16 January 2017
ISBN Information:
Conference Location: Paris, France

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