CHAPTER ONE
INTRODUCTION
1.1 BACKGROUND OF THE STUDY
In the banking system online analytical processing (OLAP) which is known to deal on transactions giving account of both single and multidimensional data has only been tied to sales, marketing, profits and times range at which these data were intensified. For sure, OLAP assists firms to know the standing of its performance. OLAP (online analytical processing) is a computing method that authorizes users to easily and carefully draw out and query data for the purpose of analyzing it from various points of view. OLAP business intelligence queries in many cases assist in trends analysis, financial reporting, sales forecasting, budgeting and other planning purposes.
OLAP is an acronym that stands for Online Analytical Processing. It is paramount and of great importance to note that the term OLAP followed the development of the standard database concept OLTP – Online Transactional Processing. OLTP close in all the daily transactions done on the operational database systems, such as, for example, a transaction reflecting a withdrawal from a checking account or a transaction creating an airline reservation. In actuality an often-used technical term for an operational database is the “OLTP system”. OLAP refers to the general activity of querying and presenting text and number data from data warehouses and/or data marts for analytical purposes. While OLTP is used in simultaneousness with traditional databases for operational (day-to-day) purposes, OLAP works (as is explained in the next section) with the data from data warehouses and data marts. Another contrast between OLAP and OLTP is that the procedure of OLTP involves “updating, querying and presenting” whereas OLAP involves only “querying and presenting”. While OLTP systems consistently perform transactions that update, modify and delete data from databases, OLAP tools are “read only”. They are used solely for the recovering of data (from analytical repositories) to be used in the decision making procedure. Users of OLAP tools can swiftly read and interpret data that is collected and structured specifically for analysis, and subsequently make fact-based decisions. Both OLTP and OLAP pre-date the Internet era. The expression “Online”, used by both of these terms, is not related with the Internet or the World Wide Web. Instead, the term “Online” in these two acronyms simply refers to a type of computer processing in which the computer responds immediately (or at least very quickly) to user requests. In today’s world, we are acquainted to the fact that the computers execute processing, updating and retrieving of data instantaneously. Howbeit, at the time the term OLTP was created, many of the computers still used devices such as magnetic tapes and punch-cards readers. The expression “Online” was used to underscore the immediacy of the results, where databases systems used a direct access type of storage (such as a hard drive) instead of a sequential access storage device (such as a magnetic tape). Before the specific OLAP functions and platforms are presented, it is important to understand the connection between the OLAP systems and the data repositories designed specifically for data analysis (i.e. data warehouses and data marts.) The next section gives a brief overview of data warehouses and data marts as they pertain to OLAP. Following the overview, the basic OLAP functionalities common across most OLAP applications are covered. The database models used by OLAP are then discussed. Next, well-known variations on the OLAP model are covered. Finally, a summary concludes the chapter by describing the overall value of OLAP. The study will therefore analyse the effect of online Analytical processing for decision support in a banking system (A case study of Citibank Lagos
1.2 Problems of the study
Some of the challenges of OLAP are pre-modeling, which is a must, great dependence on IT, poor computation capability, slow in reacting, short of Interactive analysis ability, abstract model, and great potential risk.
Another problem of OLAP is that It needs well-structured and organised information into a star or snowflake schema. You cannot have a sizable amount of dimensions during a single OLAP cube. It is not best fitted for the transactional information.
1.3 Objectives of the study
The study will analyse the effect of online Analytical processing for decision support in a banking system (A case study of Citibank Lagos). Apecific objectives include;
- To ascertain is there is a significant relationship between OLAP technology and successful decision support of banking system.
- To ascertain is there is a significant relationship between online analytical processing and performance appraisal in the Citibank Lagos.
1.4 Research Questions
- What is the relationship between OLAP technology and successful decision support of banking system?
- What is the relationship between online analytical processing and performance appraisal in the Citibank Lagos?
1.5 Research hypothesis
- There is a statistical significant relationship between OLAP technology and successful decision support of banking system.
- There is a statistical significant relationship between online analytical processing and performance appraisal in the Citibank Lagos.
1.6 Justification of the Study
Examining The study will analyse the effect of online Analytical processing for decision support in a banking system (A case study of Citibank Lagos) will provide insights into the banking industry in addressing technical issues. More so, understanding how online Analytical processing will contribute to developing effective decision support strategies to address this issue.
Ultimately, this study will contribute to the existing literature on the effect of online Analytical processing for decision support in a banking system. It will provide insights that can contribute to academic discussions and debates on the effect of online Analytical processing for decision support in a banking system. The study will be of immerse help to researchers willing to further research on the topic.
1.7 Scope of the Study
The study will focus specifically on the study will analyse the effect of online Analytical processing for decision support in a banking system (A case study of Citibank Lagos). The study will be limited to the staff of Citibank Lagos.
