The Role of Data Warehousing in Business Intelligence Systems to support rapid Decision-Making

Abstract

Business intelligence (BI) has developed into a completely new concept with the implementation of artificial intelligence (AI), providing simple and quick access to knowledge and information, data dashboards and visualizations, real-time scenarios, summary reports, and various tools for analysis of data, the web, and text. Systems used today for data management rely on data warehouses. These systems must combine, modify, and store vast amounts of data from many sources to enable analytics and business intelligence applications.  This research investigates the condition of data warehouses today and how they enhance business decision-making. This research will examine data warehouse design, implementation, management, and technical and economic problems. To give businesses an advantage in today's fiercely competitive market, the research will also examine how data warehouses affect firm productivity, including how well they can facilitate decision-making, improve data quality, and increase operational effectiveness. Two case studies will demonstrate how organizations have successfully integrated data warehouses with an applied qualitative methodology. Three business experts from the industry will speak as part of the research. After this research, a data warehouse structure that can be used across sectors will be created. The framework will also offer suggestions for implementing data warehouses in addition to data integration, governance, and quality control. The advantages and disadvantages of data warehouses, which improve business performance, will be examined in this study. Our study will enable businesses to implement better data management systems, improving business performance and offering them an edge over competitors.