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International Journal of Research and Scientific Innovation (IJRSI) |Volume X, Issue I, January 2023|ISSN 2321-2705

 Impact of Data Warehouse on Organization Development and Decision making (A Case study of United Bank for Africa and Watchlocker PLC)

Abiodun Olalere
Ecole Supérieure des Sciences, de Commerce et d’Administration des Enterprises du Benin

IJRISS Call for paper

Abstract: The study analyzes the impact of data warehouse on organizational development and decision making. A case study of United Bank for Africa. The objective of this study is to investigate the relationship between data warehouse and organization development, to investigate if the implementation of data warehouse in the organization help in minimizing inconsistency report of the organization, to investigate if data warehouse help to integrate multiple system or business into one common data source, to determine if data warehouse help to increase data security and integrity of an organization data and also to determine the impact of data warehouse on decision making of an organization. To carry out this research the survey research design was adopted and population size was 100 staffs of the above organization, we make use of a well-structured questionnaire which was administered and 84 copies was filled and returned, so a total number of 84 respondent was analyzed. The data collected was analyzed using simple percentage and frequencies. From the result of analysis it was gathered that there is a significant relationship between data warehouse and organizational development and data warehouse help to increase organization decision making.

I. Introduction

The role played by database technology in companies and enterprises has only been that of storing operational data, which is generated by daily routine operations carried out within business processes such as selling, purchasing and billing. On the other hand, managers need to access quickly and reliably the strategic information that supports decision making in an organization. Such information is extracted mainly from the vast amount of operational data stored in corporate databases, through a complex selection and summarization process. The exponential growth in data volumes made computers the only suitable support for the decisional process run by organizations. Thus, starting from the late 1980s, the role of databases began to change, which led to the rise of decision support systems that were meant as the suite of tools and techniques capable of extracting relevant information from a set of electronically recorded data. Among enterprises and organizations support systems data warehousing systems are probably those that captured the most attention from both the industrial and the academic world. Data warehouse (DW) hastens the process of retrieving information needed for decision-making. DW technology has emerged as a key source and powerful tool for delivering and accessing information for decision-makers (A. Aljanabi, A. Alhamami, and B. Alhadidi, 2013).
The concept of data warehousing was introduced in 1988 by IBM researchers Barry Devlin and Paul Murphy. The need to warehouse data evolved as computer systems became more complex and handled increasing amounts of data. Data warehousing is used to provide greater insight into the performance of a company by comparing data consolidated from multiple heterogeneous sources. A data warehouse is designed to run query and analysis on historical data derived from transactional sources, once the data has been incorporated into the warehouse, it does not change and cannot be altered since a data warehouse runs analytics on events that have already occurred by focusing on the changes in data over time. Warehoused data must be stored in a manner that is secure, reliable, easy to retrieve and easy to manage
Business Organizations can turn their data into insight and make smart, data-driven decisions with the use of data warehouse (DW), it is a digital storage system that connects and harmonizes large amounts of data from many different sources. Its purpose is to feed business intelligence (BI), reporting, and analytics, and support regulatory requirements. Data and analytics have become indispensable to businesses to stay competitive. Business users rely on reports, dashboards, and analytics tools to extract insights from their data, monitor business performance, and support decision making. Data warehouses power these reports, dashboards, and analytics tools by storing data efficiently to minimize the input and output (I/O) of data and deliver query results quickly to hundreds and thousands of users concurrently, they are solely intended to perform queries and analysis and often contain large amounts of historical data. The data within a data warehouse is usually derived from a wide range of sources such as application log files and transaction applications.