| dc.description.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.
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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. | en |
