Cis 432 Week 2 Case Study

Business Intelligence: Business intelligence is a program that coordinates the best combinations of data in sales to achieve maximum profits.

First off, what is DSS? “A decision support system (DSS) is a computer program application that analyzes business data and presents it so that users can make business decisions more easily.” (Rouse, 2010, para. 1) “It is an "informational application" (to distinguish it from an "operational application" that collects the data in the course of normal business operation).” (Rouse, 2010, para. 1) This systems data collected is usually displayed in a graphical format on the dashboard. This may comprise an “expert system or artificial intelligence”. (Rouse, 2010, para. 2)

After knowing the benefit and limitation of Decision Support System (DSS), we should consider the following points before creation of successful DSS. Even the existing system, which are away from these point, can consider the same for future enhancement. Below are most important factors to bring success to DSS while using -

Business Intelligence information consists of chronicled data, and additionally new information assembled from source frameworks as it is generated, empowering Business Intelligence supports multi-level decision making processes. Initially, Business Intelligence tools were essentially utilized by IT experts and data analysts whose job is to run analyses and generate reports with query results for business clients. Progressively, however, business administrators and workers are utilizing BI software themselves, on account of the advancement of self-administration of BI and data discovery tools

How much will organizations spend on business intelligence (BI) in 2016? According to Gartner, organizations are projected to spend almost $16.9 billion in 2016. That is an increase of 5.2% over 2015 sales . Business Intelligence plays a big role in today’s business, it now used in every part of the organization from supply chain to human resources (www.gartner.com). This paper will compare two business intelligence software tools. First, I will define business intelligence (BI). Then, I will examine the features of each of the BI tools. Next, I will discuss the pros and cons of each software. This paper will focus on the capabilities and costs for each BI software. Lastly, this paper will indicates which choice was made and an explanation of that choice.

Business intelligence applications provide new and calculative approach and helps in business development. BI results in following benefits.

Organizations collect data. This raw data must be analyzed to tease out useful information. The software used to analyze raw data is known as Business Intelligence (BI). BI is comprised of theories and processes such as data mining, online analytical processing, querying and reporting. BI improves decision making, cuts costs and identifies new business opportunities (Mulcahy, 2007). The web data extraction company, Connotate, uses BI systems, specifically dashboards, to focus on more profitable business, saving them time and money while also boosting customer satisfaction rates (6 Real Life., 2013).

There are five styles of BI as per MicroStratergy Corp. and they are: enterprise reporting(using dashboards and scorecards), cube analysis (slice-and-dice analysis), ad-hoc queries, data mining and statistics and finally alerting and report delivering. (Turban, Sharda, Delen, King, & Aronson, 2011, p. 12)

Due to the advent of small-size and low-cost computers as well as the rapid advancement of communications technology, computers have enabled management to fit information technology (IT) to the organization needs. In the commercial sector, information provided by computers is increasingly being used in decision making at all levels, but the dissatisfaction is often reported by the users. In order to solve the problem, decision support systems (DSS) are used personally by managers on an everyday basis in direct support of decisions. Along with artificial intelligence (AI) and expert systems (ES) occurred, conflict is existed between AI approach and algorithmic approach. In practice, it is hard to distinguish clearly which

complicated. It is a major mutual concern for all business and IT sector companies to change the existing situation of "mass data, poor knowledge" and support better business decision-making and help enterprises increase profits and market share. Business intelligence technologies have emerged at such challenging times. Business today has compelled the enterprises to run different but coexisting information systems.

A new trend has emerged in the modern business environment in which companies are seeking to build what is referred to as "Business Intelligence" or BI for short. This has been viewed as one of the most important organizational priorities for many organizations in the last decade and it is unlikely that this trend will end anytime in the near future. The reason for the BI is pretty clear. Companies have been collecting and warehousing various types of data for many years. BI deals with the means in which companies can make better use of the data; often in real time. This allows companies to better harness information to better support organizational goals and their business objectives. Many of the BI technologies that have developed over the years can deliver better reporting mechanisms, dashboards, and different business metrics so companies can spot various trends and gather insights that can allow the company to ultimately become more competitive. Yet, in spite of the obvious appeal of the benefits a Bi system can offer a company, the development of these systems has been a relatively slow and arduous process. This paper will introduce some of the best practices for current BI systems, as well as some of the possibilities for these systems to further develop in the future.

In the last few decades, because of availability of vast amount of data in the electronic forms, and the increase in requirements associated with its conversion into desired information, for its use in analysis of market, business management and to aid in decision process. There are many systems and technologies developed, that helped managers to make better decisions and avoid failures that are commonly associated with relying upon intuitions. Business Intelligence Systems are information systems, that are designed to allow managers to capitalize upon organization data, for the purpose of improving their decision making. They do not support the real time activities but operational ones like order processing, recording etc. The real time activities are supported by transaction processing systems. BI systems helps in managerial assessment, planning and control.

When organizations are implementing information systems with clinical decision support, they hold on to these "ten commandments" for successful clinical decision support. The creators trust that the key apparatus for health care will be data frameworks that give decision support to clients at the time they decide, which ought to bring about enhanced nature of consideration. Moreover, suppliers make numerous blunders, and clinical decision support can be valuable for finding and anticipating such mistakes. In the course of the most recent eight years the creators have actualized and examined the effect of decision support over a wide cluster of areas and have found various regular components

Decision Support Systems may comprise one or more of the systems mentioned below, which are

The developers of SSADM understood that in almost all cases there is some form of current system even if it is entirely composed of people and paper. Through a combination of interviewing employees, circulating questionnaires, observations and existing documentation, the analyst comes to full understanding of the system as it is at the start of the project. This serves many purposes.