Open Source Business Intelligence Systems

Latest advancements in information and communication technology have enabled organizations to develop innovative ways to intelligently collect data that may not be possible before. This has led to the explosion of data and unprecedented challenges in making strategic and effective use of this data for reporting towards decision making. Business Intelligent (BI) systems fill the gap by providing timely, accurate, and actionable information to the right person enabling quick and correct decisions. This book describes an open source implementation of a BI System taking a case of the Technical University of Kenya. The implementation was achieved using Hadoop cluster integrated with R statistical software. A data warehouse was developed. Various analytics were performed like student admission trends and staff distribution patterns. Challenges relating to data retrieval and Hadoop configurations were experienced. The issues in TUK are evident in other universities in Kenya. In effect, it is believed that the BI system implementation approach would be replicated in other universities in Kenya, and even other sectors of the economy like health, security, and banking, among others.

Autorentext

Ishmael N. Obonyo, M.Sc., Studied Computational Intelligence at the University of Nairobi. Specializes in Big Data, Data Analytics, Hadoop, Machine Learning. Technologist at the Technical University of Kenya, Nairobi-Kenya.