Business intelligence (BI) refers to the technical and procedural infrastructure that collects, stores and analyzes the data produced by a company's activities. BI is a broad term that encompasses data mining, process analysis, performance benchmarking, and descriptive analysis. Business forecasting naturally aligns with the BI system because business users think about their business in aggregate terms. Business analysts and other end users are also often involved in the BI development process to represent the business side and ensure that their needs are met.
Business intelligence combines a wide range of data analysis applications designed to meet different information needs. In real-time BI applications, data is analyzed as it is created, collected and processed to provide users with an up-to-date view of business operations, customer behavior, financial markets, and other areas of interest. Although the term business intelligence is sometimes synonymous with competitive intelligence (because both support decision-making), BI uses technologies, processes and applications to mainly analyze structured data and internal business processes, while competitive intelligence collects, analyzes and disseminates information with a thematic focus on the company's competitors. So I thought I'd put together some basic business intelligence concepts that should help anyone who's a little confused about the subject to clear their mental confusion.
Once all the data is connected and can “communicate with each other”, one of the next fundamental aspects of business intelligence is to make use of that data. According to Merrill Lynch, more than 85% of all business information exists on these forms; a company may only use that document once. Business intelligence (BI) comprises the strategies and technologies used by companies for data analysis and business information management. In other cases, business analysis is used more narrowly to refer to advanced analytics or more broadly to include both that information and BI.
In a world dominated by data, it's more important than ever for companies to understand how to extract every drop of value from the vast amount of digital information available at their fingertips. What became known as BI tools evolved from previous analysis technologies, often based on mainframes, such as decision support systems and executive information systems, which were mainly used by business executives. As part of the BI process, organizations collect data from internal IT systems and external sources, prepare it for analysis, query the data, and create data visualizations, BI dashboards, and reports to make analysis results available to business users for operational decision-making and strategic planning. A common example is predictive modeling, which allows the hypothetical analysis of different business scenarios.
In 1989, Howard Dresner (later an analyst at Gartner) proposed business intelligence as a general term for describing concepts and methods for improving business decision-making through the use of fact-based support systems.
