Business intelligence (BI) is the term given to the set of tools and processes used to make business decisions based on facts—instead of on guesses控制工程网版权所有, intuition, and often irrelevant experience. Few companies can afford to guess any more, so decisions based on sound data and provable relationships are critical for business survival.
　　BI, coined in the late 1990s by the IT community, has come to describe the tools used for the collection of business dataCONTROL ENGINEERING China版权所有, integration of the data across multiple dimensions, analysis of the dataCONTROL ENGINEERING China版权所有, and presentation of the results. BI tools are the preferred method for extracting information and correlations from massive databases of customer and sales data. BI analysis typically focuses on data about sales, customers, suppliers, shipments, purchase orders, invoicesCONTROL ENGINEERING China版权所有, and deliveries.
　　The manufacturing equivalent of business intelligence is manufacturing intelligence (MI). Most manufacturing companies have engineers with considerable knowledge and experience in extracting information and correlations from production data using data historians and associated analysis tools. MI expands the concepts of traditional studies by looking across multiple dimensions of production information to discover correlations not seen in normal engineering analysis.
　　Multi-dimensional dataCONTROL ENGINEERING China版权所有, query
　　MI focuses on products, inventory, work in process (WIP), production schedules, production performance, yields控制工程网版权所有, waste, and costs. MI usually does not need the high resolution data collected in data historians. The typical MI timeframe may be a production step, duration of a production run控制工程网版权所有, or length of a batch operation. Like BI, MI is based on multi-dimensional data and advanced query and reporting systems.
　　Multi-dimensional data is maintained in “facts” and “dimension” tables. Facts are measurable pieces of information, such as a production yield or product quality measure. Each fact is associated with multiple dimensions, such as time, batch number, production