Data Warehousing Solutions for Scalable Etl Pipelines

Authors

  • Harish Goud Kola   Independent Researcher, USA

Keywords:

Abstract

Conventional ETL are ‘batch type’ meaning the extraction of data from source systems, transformation and loading into a central analytical data warehouse was timed and periodic. However, due to the emergence of real-time analytics, there is a shift to streaming ETL because organisations require insights in real time. As the mass of incoming data rises, more attention is paid to the scalability of ETL processes in order to secure high efficiency, agility, and fault tolerance.

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International Journal of Scientific Research in Science, Engineering and Technology

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Published

2018-05-30

Issue

Volume 4, Issue 8, May-June-2018

Section

Research Articles

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Copyright (c) IJSRSET

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This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

[1]
Harish Goud Kola "Data Warehousing Solutions for Scalable Etl Pipelines" International Journal of Scientific Research in Science, Engineering and Technology (IJSRSET), Print ISSN : 2395-1990, Online ISSN : 2394-4099, Volume 4, Issue 8, pp.762-769, May-June-2018.