Abstract
The approach to decision support as an individual system has been replaced by a new viewpoint of intelligent software and systems. Based on this new approach, enterprise systems are designed to have business intelligence (BI) as an umbrella concept that covers various enabler tools and capabilities in the form of non-functional requirements. The current state of the art in decision support takes the intelligence requirements of enterprise systems as important quality aspects into consideration, along with their functional and non-functional needs, but the literature lacks studies on the evaluation of these intelligence requirements. In this chapter, business intelligence and enterprise systems literature are reviewed. Also based on the latest researches, the position of BI on these systems is discussed. In the following, through the study of BI capabilities and proposing them as non-functional, the BI impacts on the design of enterprise systems and software are described along the directions for future research and insights for information systems development.
TopBackground
In this chapter, it will be given literature review about business intelligence and enterprise systems. The lack of a large number of researchers will limit this work on newer research period.
Business Intelligence
The term Business Intelligence was introduced to describe a set of concepts and methods to improve business decision-making by using fact-based, computerized decision support systems. This term is introduced by Howard Dresner of the Gartner Group (Nylund, 1999). The first definition introduced BI as a management philosophy and tool that help organizations to manage and refine business information to make effective decisions (Gbosbal & Kim, 1986).
Business intelligence presents the process through which organizations take advantage of virtual and digital technology to collect, manage and analyze structural or non-structural data. In other words, the technology and commercial processing procedures in the decision-making are supported through the extraction, integration and analysis of data (Berson & Smith, 1997).
The purpose of business intelligence is to help control the resources and the information flows of the business which exists in and around the organization. BI makes a large contribution to the required intelligence and knowledge of the organizations’ management by identifying and processing data in order to explain their hidden meanings (Azoff & Charlesworth, 2004).
As a total definition, Lönnqvist & Pirttimäki (2006) stated that “Business intelligence as a term can be used when referring to the following concepts”:
- 1.
Related information and knowledge of the organization, which describe the business environment, the organization itself, the conditions of market, customers and competitors and economic issues;
- 2.
A system and a systematic process by which organizations obtain, analyze and distribute the information for making decisions about business operations.
Eckerson realized that business intelligence must be in able to provide the production reporting tools, end-user query and reporting tools, on-line analytical processing (OLAP), dashboard/screen tools, data mining tools and planning and modeling tools (Eckerson, 2010).
Bose (2009) believed that the role of BI is preparing the right information to the right people at the right time to improve decision making, hence improve managerial proceeding and enterprise performance. Generally, the main focus in managerial approach is on the process of gathering data from internal and external sources and of analyzing them to produce relevant information to the decision making process (M. Ghazanfari, Jafari, & Rouhani, 2011; Petrini & Pozzebon, 2009). In technological point of view, BI has been proposed as an instrument of analysis, providing automated decision making about business conditions, sales, customer demand, product preference, and so on. It uses a different type of analysis and mathematical, statistical and artificial intelligence, as well as data mining and OLAP to take a decision in more suitable format (M. Ghazanfari, et al., 2011; Petrini & Pozzebon, 2009). Ghazanfari et al. (2011) and Rouhani et al. (2012) claimed that there is one more approach in BI definition called system enabler in which the main focus is on value added features on supporting information.
Key Terms in this Chapter
Enterprise System: Enterprise system (ES) is large-scale application software package that support business processes, recourse management, information flows, reporting, and data analytics in complex organizations and in scale of enterprise.
Requirement: A requirement is a singular documented physical and functional need that a particular design, product or process must be able to perform. It is a statement that identifies a necessary attribute, capability, characteristic, or quality of a system for it to have value and utility to a customer, organization, internal user, or other stakeholder.
System Design: Systems design is major phase of information system development and is the process of defining the architecture, components, modules, interfaces, and data for a system to satisfy specified requirements.
Business Intelligence: Business intelligence, or BI, is an general term that refers to a range of capability and tools used to analyze an organization’s raw data and transform them to actionable knowledge by data mining, online analytical processing, querying, reporting and so on.
Functional Requirement: Functional requirement that define specific behavior or function of system which come from business needs. The plan for implementing functional requirements is detailed in the system design.
Nonfunctional Requirements: A non-functional requirement is a system requirement that specify criteria that can be used to judge the operation of a system, rather than specific behaviors. These requirements determine the quality of the system or software. The plan for implementing non-functional requirements is detailed in the system architecture.