The term business intelligence (BI) is generally used to describe a type of information system which is designed to help decision-makers spot trends and relationships within large volumes of data. Typically, business intelligence software is used in conjunction with large databases or data warehouses. While the specific capabilities of BI systems vary, most can be used for specialized reporting (e.g., summarizing data along multiple dimensions simultaneously), ad-hoc querying, and trend analysis.
As an example, consider a large grocery store chain. Similar to most competitors, the store keeps track of all purchases, down to the item category level. By that, we mean that the store keeps track of all the items that are purchased together (e.g., a package of diapers, a bag of potatoes, etc.) on a single receipt. The detailed data is captured and stored in a large database (and possibly copied into a data warehouse). Once that data is available, data analysts use business intelligence software to try and identify products that seem to be purchased together (which can help in product placement decisions), evaluate the success of marketing promotions, and so on.
When you consider the extent of the data that is captured at a check out, (goods purchased, prices, combinations, what is not purchased, date and time, how payment was made, and that much of that data can be combined with other data such as information available about the purchaser on loyalty cards, advertising campaigns, weather, competitors activities etc.) you begin to see the extent of the possibilities.
As with knowledge management systems, the value of business intelligence systems can be hindered in several ways. The quality of the data that is captured and stored is one concern. In addition, the database (or data warehouse) might be missing important data (for example, the sales of ice cream are probably correlated with the temperature; without temperature information, it might be difficult to identify why sales of ice cream increase or decrease). A third challenge can be that while data analysts may know how to use the BI software, they may not know too much about the context for the organizations operations. In contrast, a manager may know the organization, but not know how to use the BI software. As a result, it is not uncommon to have a team (a manager paired with a data analyst) to try and get the most information (and/or knowledge) out of a business intelligence system.
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