Business intelligence is also known as BI.
When it comes to the term "business intelligence", it is generally believed that Gartner first proposed it in 1996, but in fact, Hans Peter Luhn, a researcher at IBM, used this concept as early as 1958. He defined "intelligence" as "the ability to understand the relationship between things and rely on this ability to guide decision-making to achieve the desired goals."
In 1989, Howard Dresner described business intelligence as "a set of theories and methods for improving business decisions using fact-based decision support systems." [1] Business intelligence is generally understood as a tool that transforms existing data in an enterprise into knowledge and helps the enterprise make wise business decisions. The data here includes orders, inventory, transaction accounts, customers and suppliers from the enterprise's business system, data from the industry and competitors of the enterprise, and various data from other external environments of the enterprise. The business decisions that business intelligence can assist can be either operational, tactical or strategic. In order to transform data into knowledge, it is necessary to use technologies such as data warehouses, online analytical processing (OLAP) tools and data mining. Therefore, from a technical perspective, business intelligence is not a new technology. It is just a comprehensive application of technologies such as data warehouses, OLAP and data mining.
Business intelligence can be considered as the process of collecting, managing and analyzing business information, with the goal of enabling decision makers at all levels of the enterprise to gain knowledge or insight, so that they can make decisions that are more beneficial to the enterprise. Business intelligence generally consists of data warehouse, online analytical processing, data mining, data backup and recovery, etc. The implementation of business intelligence involves software, hardware, consulting services and applications, and its basic architecture includes three parts: data warehouse, online analytical processing and data mining.
Therefore, it is more appropriate to regard business intelligence as a solution. The key to business intelligence is to extract useful data from many different enterprise operating systems and clean them to ensure the correctness of the data. Then, after the extraction, transformation and loading (ETL process), merge them into an enterprise-level data warehouse to obtain a global view of the enterprise data. On this basis, use appropriate query and analysis tools, data mining tools (big data magic mirror), OLAP tools, etc. to analyze and process them (at this time, information becomes knowledge to assist decision-making), and finally present the knowledge to managers to support their decision-making process.
Well-known IT vendors that provide business intelligence solutions include Microsoft, IBM, Oracle, SAP, Informatica, Microstrategy, SAS, Royalsoft, etc.