Data Mining and Business Intelligence Dashboards

Today, the most successful companies are those that can respond quickly and flexibly to market changes and opportunities. A detailed understanding and knowledge is required to analyze the business environment at different levels. This can be achieved by implementing value added information throughout the organization. There has been an increased demand in the development of IT that performs data manipulation operations to report and analyze the data. While sifting through all that data, organizing it, and then using it to make the business run more profitably has become a bigger challenge. Decision markers can use such information to implement business strategies that best meet the needs of the ultimate customer. Making use of that information is all the more urgent. DOI: 10.4018/jabim.2012100104 40 International Journal of Asian Business and Information Management, 3(4), 39-44, October-December 2012 Copyright © 2012, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited. DATA WAREHOUSES The purpose of a data warehouse is to establish a repository that makes operational data accessible in a form readily acceptable for analytical processing activities, such as EC applications, decision support, and other end-user applications. As part of this accessibility, detail-level operational data must be transformed into a relational form, which makes them more amenable to analytical processing. Thus, data warehousing is not a concept by itself, but is interrelated with data access, retrieval, analysis, and visualization. Not all data are transferred to the data warehouse, and frequently only a summary of the data is transferred in a process of extraction, transformation, and load (ETL). The data that are transferred are organized within the warehouse as a relational database so that it is easy for end users to access. Also, the data are organized by subject, such as by product, customer segment, or business partner. EC data also may be organized according to a business process, such as ordering, shipping, or available inventory. The data then can be optionally replicated in data marts DATA ANALYSIS AND KNOWLEDGE DISCOVERY Once the data are in the data warehouse and/ or data marts, they can be accessed by end users. Users can then conduct several types of analytical activities with the data, ranging from decision support and executive support analyses to ad-hoc queries, online analytical processing (OLAP), and data mining. Operational data store: A database for use in transaction processing (operational) systems that uses data warehouse concepts to provide clean data.