Cheryl Ann Alexander¹* and Lidong Wang²

¹Institute for IT innovation and Smart Health, Mississippi, USA
²Institute for Systems Engineering Research, Mississippi state university, Vicksburg, USA

*Corresponding Author: Cheryl Ann Alexander, Institute for IT Innovation and Smart Health, Mississippi, USA.

Received: January 16, 2023; Published: February 18, 2023

Abstract

Data Warehousing is data-driven by society. Society is data-driven, making the process of making business decisions both difficult and data-driven. Organizations use many processes to determine what business decisions would be best for them, each of them capable of processing huge amounts of data and assisting the management in decision-making. For decades, the only business intelligence process in play has been data warehouses. Now, however, Big Data has made it possible to expand and modernize to support other data sources capable of centralizing heterogeneous data in a manner that expands the variety and dynamics of data such as data lakes, the cloud, etc.

Keywords: Data Warehousing; Big Data; Data Analysis; Cloud; Machine Learning; Cybersecurity

References

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Citation

Citation: Cheryl Ann Alexander and Lidong Wang. “Data Warehousing: A Literature Review on Effective Implementation Approaches". Acta Scientific Computer Sciences 5.3 (2023): 66-71.

Copyright

Copyright: © 2023 Cheryl Ann Alexander and Lidong Wang. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.