Evolution of Business Intelligence System: From Ad-Hoc Report to Decision Support System to Data Lake Based BI 3.0

Abstract

Business intelligence (BI) characterizes the ability to understand, recognize, and adapt to fresh business goals, to resolve business complications, and to understand new business conditions. The BI system works on previously collected data from different public and business sources and analyzes the data to notice and control various legalities to streamline decision-making. BI has some analytical tools to work on operational data (day-to-day operations business data), collected from different sources, to offer complex and extremely important information to business managers, senior executives, and business planners. The foremost goal of BI is to enhance the quality of information and timeliness in the decision-making process, to understand the various opportunities presented in business firms like market demand, market trends, risks, product competitions, future decisions, etc. BI may be defined as a key concept describing a blend of tools, infrastructure, processes, applications, preparation, and procedures to gather data, provide best practices, and analyze operational data to provide strength in decision-making events in big organizations. Although in the current market scenario BI is consider to be the backbone of the enterprise system and intelligent business, the phrase BI was first coined in 1865 by Richard Millar Devens in the Cyclopedia of Commercial and Business Anecdotes, where he was trying to explain how Sir Henry Furnese made a huge profit by gathering information and acting on that information system in a banking application. In late 1958, IBM gave a brief definition of BI as collecting data on the uses of technology and analyzing data to transform or translate the data into useful information. After IBM defined BI, many researchers and organizations started working in this field and invented the decision support system (DSS). Many researchers think that the modern BI system evolved from DSS. DSS is defined as a combination of hardware and software that provides support to the top-level executive of the organization for decision-making. DSS is also known as an informational system. In late 1970, the first DSS was introduced, known as management information system (MIS). MIS planned to offer decision-making information to the management of organization to control, evaluate, and plan different activities within the organization. In the 1970s, a new term was coined, executive information system (EIS), also known as executive support system (ESS). EIS or ESS is an example of DSS, which provides assistance to the senior-level executive of a corporation for decision-making. Researcher Bill Inmon started working on in-house analysis of data in the 1980s and gave the term “data warehouse”. The current BI system is well-known to belong to the prior research on the alike system, known as DSS, MIS, ESS, or EIS. Today, organizations invest a huge amount of money in BI systems because businesses need multidimensional analysis of data. To fulfill the market demand and stay in competition, businesses need descriptive analysis, predictive analysis, and prescriptive analysis. The current BI system, known as BI 3.0, offers all types of analysis. This chapter describes the past, present, and future of BI with current BI architecture. This chapter also gives a direction for future research in BI with advanced analytics.