An integrated approach to deploy data warehouse in business intelligence environment

Abstract

Business Intelligence (BI) provides historical, current and predictive views of business operations with the help of some technologies, that include reporting, online analytical processing, analytics, data mining, process mining, complex event processing, business performance management, benchmarking, text mining, predictive analytics and prescriptive analytics. As analytics plays a major role in BI, OLAP is an integrated part of BI in modern day business application. Data warehouse is the most popular way to design and build OLAP. Data warehouse along with ETL and reporting tools provides an integrated environment for business processing. Business processing also demands decision making system and knowledge representation. Moreover the data sources are physically distributed in different locations. Hence modern day business environment is a complex architecture with a numbers of entities. In this paper authors present an integrated architecture to manage and design business intelligence environment by co-ordinating several associated entities to achieve business agility.

An Integrated Approach to Collaborate Web Usage Mining and Business Intelligence for Recommendations in E-Commerce.

“…Business Intelligence (BI) refers to the ability to collect and analyze huge amount of data pertaining to the customers, vendors, markets, internal processes, and the business environment. Business Intelligence (BI) provides historical, current and predictive views of business operations with the help of some technologies that inc lude reporting, online analytical p rocessing, analytics, data min ing, process mining, co mplex event processing, business performance management, benchmarking, text min ing, predictive analy t ics and prescriptive analytics [3].…”