The term Business Intelligence was first coined by IBM researcher Hans Peter Luhn in 1950. It refers to the "ability to apprehend the interrelationships of presented facts in such a way as to guide action towards a desired goal."
Business Intelligence, BI is a concept that usually involves the delivery and integration of relevant and useful business information in an organization. Companies use BI to detect significant events and identify/monitor business trends in order to adapt quickly to their changing environment and a scenarios.
One of the most important reasons why you need to invest in an effective BI system is because such a system can improve efficiency within your organisation and, as a result, increase productivity and profitability.
Business intelligence (BI) is the use of software, tools, and applications to analyze an organization’s raw data with the goal of optimizing decisions, improving collaboration, and increasing overall performance. The process is the collection and analysis of personal, team, and organizational information through activities such as data mining, analytical processing, querying, and reporting..
In a 1958 article in the IBM Journal called A Business Intelligence System (PDF), Hans Peter Luhn, a researcher for the company, used the term in relation to the definition of “intelligence” in Webster’s dictionary:
"The ability to apprehend the interrelationships of presented facts in such a way as to guide action towards a desired goal".
From the 1960s to the mid-1980s, decision support systems (DSS) were created and deployed so that executives could use computer-aided models to assist with corporate decision making and planning. DSS led to data warehousing and then analytics processing and then finally the rise of “business intelligence” as a standalone discipline.
In 1989, Howard Dresner, a consultant who would later become a Gartner analyst, proposed the use of the umbrella term “business intelligence” to refer to “concepts and methods to improve business decision-making by using fact-based support systems.”
In general terms, business intelligence empowers executives to make better and more profitable decisions in terms of how to cut costs, see new opportunities, react quickly to news and other developments, make processes more efficient, gain competitive advantages, obtain leverage in relationships and negotiations, and optimize price points.
At its core, business intelligence is the use of data to answer questions such as these:
What has happened?
What is happening?
Why is it happening?
What will happen?
What do we want to happen?
The answers can often be found through historical data analysis (whether descriptive, predictive, or prescriptive) or real-time analytics based on the information in locations and activities including customer databases, supply chains, personnel records, manufacturing data, and sales and marketing campaigns. BI analysis aims to pull relevant data from such sources to help executives to drive business value through actions such as cutting costs or increasing revenues. Historical trends are often examined to create long-term strategic decisions while real-time data can support immediate, tactical decisions.
That data is often stored in internal data warehouses or private clouds but is increasingly saved off-site in public clouds such as Amazon Web Services, Microsoft Azure, or Google Cloud Platform. (See our comparison of the two most popular public clouds: Azure vs. AWS.) Apache Hadoop, an open-source software framework used for distributed storage and processing large sets of data, is another increasingly popular option.