Wednesday, 2 March 2022

Study on Data Warehousing Applications: An Analytical Tool for Decision Support System | Chapter 04 | Recent Recent Advances in Mathematical Research and Computer Science Vol. 8

 This paper gives an overview of data warehousing technologies, with a focus on the unique demands that data warehouses make on database management systems (DBMSs). Data warehouses and other data-driven decision support systems can handle data extraction from a variety of sources. Data warehouses standardise data throughout the enterprise to provide a unified picture of data. Decision makers can get the information they need from data warehouses (DW). On-line analytical processing (OLAP) applications are supported by the data warehouse, and their functional and performance requirements are considerably different from those of the on-line transaction processing (OLTP) applications typically supported by operational databases. Data warehouses enable effective data mining by providing on-line analytical processing (OLAP) tools for interactive analysis of multidimensional data at various granularities. Data warehousing and OLAP have evolved as major technologies for storing, organising, and retrieving large amounts of data. Both are critical components of decision assistance, which has become a hot topic in the database business.

This study examines the characteristics, uses, and architecture of data warehousing (DW) using Data Mining, Online Analytical Processing (OLAP), and On-line Transaction Processing (OLTP) technologies.


Author(S) Details

Mohammed Shafeeq Ahmed
Department of Computer Science, Gulbarga University, Gulbarga, Karnataka, India.

View Book:- https://stm.bookpi.org/RAMRCS-V8/article/view/5744

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