Implementation of Star Schemas from ER Model

Chandwani, Gunjan; Uppal, Veepu; Rachna, Manav

doi:10.14257/ijdta.2015.8.3.10

Cited by 4 publications

(1 citation statement)

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“…They correspond to events that always occur in the organization or company [14]; • The measures of the fact table should be numeric and additives (at worst semiadditives) [15]; • The data of a fact table are fixed and cannot be changed [16];…”

Section: Rules For Fact Tables and Measuresmentioning

confidence: 99%

X-ETL: A Data-Driven Approach for Designing Star Schemas

Moukhi

Azami

Mouloudi

et al. 2019

Int. J. Recent Contrib. Eng. Sci. IT

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The data warehouse design is currently recognized as the most important and complicated phase in any project of decision support system implementation. Its complexity is primarily due to the proliferation of data source types and the lack of a standardized and well-structured method, hence the increasing interest from researchers who have tried to develop new methods for the automation and standardization of this critical stage of the project. In this paper, the authors present the set of developed methods that follows the data-driven paradigm, and they propose a new data-driven method called X-ETL. This method aims to automating the data warehouse design by generating star models from relational data. This method is mainly based on a set of rules derived from the related works, the Model-Driven Architecture (MDA) and the XML language.

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Section: Rules For Fact Tables and Measuresmentioning

confidence: 99%