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Introduction to the steps of business intelligence implementation


  The essence of business intelligence (BI) is a technology that can effectively extract information from data, discover knowledge from that information in a timely manner, and provide support for decision making.

商业智能

        Business intelligence is often understood as a tool that transforms the data available in an enterprise into knowledge and helps the enterprise make informed business decisions. The data referred to here includes orders, inventory, transaction accounts, customers and suppliers from an organization's business systems, data from the industry in which the business operates and from competitors, and data from other external environments of the business. Business intelligence helps business manage decisions that can be operational, tactical and strategic, and in order to turn data into knowledge, we need to use technologies such as data warehousing, online analytical processing (OLAP) tools, and data mining. Therefore, technically speaking, BI is not a new technology, but a comprehensive application of data warehousing, OLAP and data mining technologies.

  The implementation of business intelligence system is a complex system project. The whole project involves a variety of knowledge such as enterprise management, operation management, information system, data warehouse, data mining, and statistical analysis. Therefore, in addition to choosing the right BI software tools, users must also follow the right implementation methods to ensure the success of the project. The implementation steps of a business intelligence project can be divided into:

  (1) Requirements analysis: Requirements analysis is the first step in the implementation of business intelligence. The expectations and needs of the enterprise for BI need to be clarified before other activities are carried out, including the topics to be analyzed and the possible perspectives (dimensions) of each topic; we need to discover the laws of these aspects of the enterprise. The needs of the user must be clear.

  (2) Data warehouse modeling: Through the analysis of enterprise requirements, the logical and physical models of the enterprise data warehouse are established, the application architecture of the system is planned, and various types of enterprise data are organized and classified according to the analysis themes.

  (3) Data extraction: After the data warehouse is established, data must be extracted from the business system to the data warehouse, and the data must be converted and cleaned in the extraction process to meet the needs of analysis.

  (4) Establishment of business intelligence analysis reports: business intelligence analysis reports need to be developed by professionals in accordance with the format set by the user, or the user can develop it himself (the development method is simple and fast).

  (5) User training and data simulation testing: for the development-use separation of the business intelligence system, the end-user is quite simple to use and can analyze specific business problems with a click.

  (6) System improvement and refinement: The implementation of any system must be continuously improved. This is especially true for business intelligence systems. Users may make more and more specific requests after using it for some time. This is when the system needs to be refactored or improved according to the steps above.

  

 

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