Business Intelligence: Escalation of Data Warehousing and Data Mining for effective Decision Making
In this modern era of globalization and high level of integration, new techniques, models and tools supporting Artificial Intelligence (AI), Internet of Things (IoT) and wireless internet devices have changed the concept of Business Intelligence (BI) by providing easy and quick access to information and knowledge, real time scenarios, data visualizations and dashboards, summary reports, and other analytical tools for data, text and web mining. The process of data analysis to obtain actionable information with the help of technological tools and software is termed as Business Intelligence. Now, data and information are treated as an important asset in an organization to impart quality and summarized knowledge for valuable, quick and effective decisions and to be the leader in their market segment. Large repositories of past databases are managed in organizations as Data Marts or/ and Data Warehouse (DW) which are continuously queried and searched by Data Mining (DM) tools for new patterns, insights and findings that aids not only in current decisions but also for future decisions, tactical and operational planning. A Decision Support system (DSS) is an automated tool that provides summary reports for judgements and actions in an organization. It acts as business performance software and helps the managers to take sound decisions by providing facts and figures in summary formats. It is extensively used in business and management to provide Executive dashboard, identification of negative trends and loopholes, better allocation of business resources and faster decision making. This paper explores how Data Warehousing and Data Mining are contributing to Business Intelligence and are collectively utilized for effective decision making and smooth operations of an organization. Furthermore, challenges, limitations and applications of analytical tools for DW, DM, BI and DSS will also be discussed.