Enterprise Data Warehouse Design Considerations

In this Journal, the base lines for designing an Enterprise Data Warehouse (EDW) to support business analytics in the era of “big data” has been explained. The scope and challenges of building and evolving a very stable and successful EDW architecture to meet new business requirements. These include extreme integration, semi- and un-structured data sources, and petabytes of behavioral data as well as massively parallel relational databases, and then structuring the EDW to support advanced analytics.

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2024-08-04
DOI
https://doi.org/10.5281/zenodo.13209821
Primary Topic
Skin and Cellular Biology Research
Type
article
Field-Weighted Citation Impact
0.00
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article

Enterprise Data Warehouse Design Considerations

Zenodo (CERN European Organization for Nuclear Research)
Skin and Cellular Biology Research
article

Enterprise Data Warehouse Design Considerations

article en

Abstract

In this Journal, the base lines for designing an Enterprise Data Warehouse (EDW) to support business analytics in the era of “big data” has been explained. The scope and challenges of building and evolving a very stable and successful EDW architecture to meet new business requirements. These include extreme integration, semi- and un-structured data sources, and petabytes of behavioral data as well as massively parallel relational databases, and then structuring the EDW to support advanced analytics.

Zenodo (CERN European Organization for Nuclear Research)
Industry, innovation and infrastructure
Openalex Percentile: Top 61%
Skin and Cellular Biology Research
DOIOpen Access PDFOpenAlex
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Enterprise Data Warehouse Design Considerations · Zenodo (CERN European Organization for Nuclear Research) (2024) | TGRS Research Map | TGRS