Leveraging Data Mining and Data Warehouse to Improve Prison Services and Operations in Nigeria

Abstract

Crimes are social nuisance and cost our society dearly in several ways. In Nigeria, any research geared towards helping to solve crimes faster will be beneficial to the society at large. It has been observed that the major challenge facing all law-enforcement and intelligence-gathering organizations in Nigeria is how to accurately and efficiently analyze the growing volume of crime data. As the volume of this crime data becomes enormously large, new techniques have to be used to turn this data into valuable information and actionable knowledge so that appropriate actions can be taken accordingly. Sometimes it is usual to find that the data needed to be analyzed to produce report are scattered throughout different operational States and jurisdictions of Nigeria and must first be carefully integrated. Moreover, observations show that the process required to extract the existing data from each operational system demand so much of the system resources such that the IT professional must wait until nonoperational hours before running targeted queries required for producing operational reports. These delays are not only time-consuming and frustrating for both the IT professionals and the decision-makers they are dangerous for the sector whose primary task is to control crime spread and explosion. It should be noted that when such operational reports are finally produced, they may not be relied upon, because the data use in producing them many a times are inconsistent, inaccurate, or obsolete. This paper therefore highlights the increasing growing need for Data integration, Data warehouse and Data mining as ways to improve the operations of principal actors within the prisons sector of Nigeria. The paper explains what these Data management techniques mean and entail, and furthermore suggests ways to effectively leverage the techniques to help detect existing crime patterns and speed up the process of solving crimes.

Keywords: Crime-data, data mining, data mining techniques, data warehouse, data integration