A study of data analysis using OLAP Technology

Abstract

The problem addressed in this project is the use of On Line Analytical Processing (OLAP) technology in data analysis. It is discussed in the context of a power utility company with the objective of demonstrating how this technology can be used to analyse the massive amounts of data held in relational database systems. Relational database systems are well suited for On Line Transaction Processing (OLTP) systems but are inadequate for interactive multi-dimensional reporting and analysis offered by OLAP. In this project, data is analysed using roll up, drill down, trend and forecasting analysis. The multi-dimensional database analytical engine used is Personal Express 6 and the client application that displays the data in different formats is Oracle Express Objects. The results obtained show that, although OLTP systems hold large amounts of data, the challenge is to get a system that can effectively integrate and distill data into information for decision making. OLAP extends the capacity of decision makers, to process mountains of data encountered in the process of making decisions. It provides the decision maker exploration avenues that might otherwise go unnoticed or be deemed too complex and difficult to pursue. Given the shrinking window of opportunity associated with the pace of business, OLAP may provide the competitive advantage to advance an organization past its competitors or at least to stay abreast of the market place. ; In the case of the power utility company, OLAP's forecasting capability based on statistical methods is a good way to predict future sales based on historical data. Based on the observations made during the project, the power utility company may use OLAP technology in more areas apart from sales analysis. Some of these areas include predicting use of stock items in stores and financial transactions over time.