 Posted: Mon 8:18, 18 Apr 2011 Post subject: Business Intelligence to enhance the level of ente |
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| Business Intelligence to enhance the level of enterprise information (1)
Chinese papers League finishing. Abstract enterprise information is continuously advancing to the depth and breadth of two-way, appropriate information technology is constantly evolving, business intelligence as a new information technology in business has been widely used in information technology, this paper business Smart how to improve enterprise information and applications in the enterprise model are discussed. Key words business intelligence enterprise information competitiveness With the development of global information in the world, all walks of life has set off a wave of information technology, information of the level is also evolving, from the MRP, MRPII, ERP to CRM, from the data warehouse to data mining, each change has greatly promoted the upgrading of information technology companies and enterprise management level, powerful, for transactional information systems in the large number of applications in various industries. However, these applications are concentrated in the front end of the data query, storage and simple processing. Now enterprises have accumulated large amounts of business data, research has shown that an average of 18 months,mbt laarzen, doubling the amount of information, but can analyze the data estimated that only 7%. How to convert large amounts of data and reliable information to tap the potential business opportunities, has become a growing concern. As a result, Business Intelligence (Business Intelligence, referred to as BI) technologies have emerged. This article on how to improve business intelligence and enterprise information applications in the real model of the enterprise. 1 stage model of enterprise information Harvard University professor Richard Nolan (Richard.Norlan) first proposed the development of information systems 4 stages, the development period of popularity , control and maturity, which is in chronological order the establishment of four-stage model. To the 20th century, late 80's, expanding the use of information systems at this time Nolan has also filed a six-stage model. The initial phase, spread of, control of the integration period, data management, and maturity. Nolan has become the description of this model the degree of development of enterprise information a powerful tool, is a more successful model, which at the conceptual level on the overall enterprise information systems planning, information technology planning process and measure the enterprise in which a message development stage and so provide an important reference. But with the information age, it was found Nolan model has its limitations, not only from the acceptance of computer technology development and to evaluate the level of computer management information system processes, and effective allocation of resources from the information and data to effectively manage , effective system integration, or even go from the specific implementation of enterprise information starting, so the industry appears generally accepted four-stage model of enterprise information, these four stages are: a single department of information, inter-departmental information technology, business level information technology, information industry chain level. The following table: see this four-stage model, are based on information technology enterprises in the process, companies can implement their own specific circumstances of information, step by step in accordance with the Nolan models do not have the six stages. In the modern enterprise informatization process, must be combined with technology, management, and cultural factors gradual manner, so that the new intelligence technology into the enterprise management. 2 business intelligence business intelligence content of the term in 1989 by Gartner Group's Howard Dresner was first proposed, it describes a series of concepts and methods, through the application of fact-based support system to assist business decision making. Data warehouse Institute Organization that . Simply put, business intelligence is a business information collection, management and analysis process is intended to enable companies to acquire knowledge and insight at all levels of decision-makers, prompting them to make the enterprise more profitable decisions. In fact, business intelligence is not new technology, it's just data warehousing, OLAP and data mining technologies such as integrated use. To this end, the business intelligence as a solution should be more appropriate. To in-depth understanding of business intelligence, business intelligence organization must understand the system. Business intelligence organizational structure mainly by the data warehouse system, OLAP and data mining of three parts. Data warehouse system in accordance with WHInmon the terms of the construction authority of the designers said, . This short but comprehensive definition points out that the main features of the data warehouse in four key words: subject-oriented (subject-oriented), integrated (integrated), time-varying (time-variant), nonvolatile ( nonvolatile), data warehouse and other data storage systems (such as relational database systems, transaction processing systems and file system) to distinguish. OLAP (Online Analytical Processing, referred to as OLAP) is a type of software technology, which help analysts, managers or executives can be observed from the perspective of many possible in the transformation from the original data out, can really users to understand, and truly reflect the characteristics of business information dimensions for fast, consistent, interactive access, to gain a deeper understanding of the data. Data mining is in accordance with certain rules of the database and data warehouse of information in the existing data mining, excavation and analysis, from identifying and extracting hidden patterns and interesting knowledge, and use them to provide scientific basis for decision-makers. Data mining task is to find patterns from the data. There are many models, according to the functions can be divided into two categories: predictive (Predictive) model and describe the type (Descriptive) mode. |
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