The term business intelligence (BI) dates to 1958.
BI describes a set of concepts and methods to improve business decision making by using fact-based support systems. BI is sometimes used interchangeably with briefing books, report and query tools and executive information systems. Business Intelligence systems are data-driven DSS.
BI systems provide historical, current, and predictive views of business operations, most often using data that has been gathered into a data warehouse or a data mart and occasionally working from operational data. Software elements support reporting, interactive "slice-and-dice" pivot-table analyses, visualization, and statistical data mining. Applications tackle sales, production, financial, and many other sources of business data for purposes that include, notably, business performance management.

BI technologies
Prior to the start of the Information Age in the late 20th century, businesses had to collect data from non-automated sources. Businesses then lacked the computing resources to properly analyze the data, and as a result, companies often made business decisions primarily on the basis of intuition.
As businesses started automating more and more systems, more and more data became available. However, collection remained a challenge due to a lack of infrastructure for data exchange or to incompatibilities between systems. Analysis of the data that was gathered and reports on the data sometimes took months to generate. Such reports allowed informed long-term strategic decision-making. However, short-term tactical decision-making continued to rely on intuition.
Thus we have business intelligence, a term and a definition that date to a seminal October 1958 IBM Journal article by Hans Peter Luhn titled A Business Intelligence System.

History
Business intelligence often uses key performance indicators (KPIs) to assess the present state of business and to prescribe a course of action. Examples of KPIs are things such as lead conversion rate (in sales) and inventory turnover (in inventory management). Prior to the widespread adoption of computer and web applications, when information had to be manually inputted and calculated, performance data was often not available for weeks or months. Recently, banks have tried to make data available at shorter intervals and have reduced delays. The KPI methodology was further expanded with the Chief Performance Officer methodology which incorporated KPIs and root cause analysis into a single methodology.
Businesses that face higher operational/credit risk loading, such as credit card companies and "wealth management" services, often make KPI-related data available weekly. In some cases, companies may even offer a daily analysis of data. This fast pace requires analysts to use IT systems to process this large volume of data.