Business Intelligence (BI) currently refers to technologies, applications and practices that covers the processes and methods of collecting, storing and analysing data from business operations or activities to optimise performance. All of these things come together to create a comprehensive view of a business to help people make better, actionable decisions.

How we see BI today is very different from how it originated. BI has been developing for over 150 years. The term “business intelligence” was first used by Mr. Richard Miller Devens, in his book “Cyclopaedia of Commercial and Business Anecdotes” which was first published in 1865. He described how Sir Henry Furnese, an extremely successful banker, profited from information by actively collecting and acting on it before his competition. This pointed out the fact that it was far more reliable to use data and empirical evidence, as opposed to gut instinct, to develop a business strategy.

During the last decade of the 1800s, Frederick Taylor introduced the first formalized system of business analytics in the USA. His system of scientific management began with time studies that analysed production techniques and laborers body movements to find better efficiencies that increased industrial production. Soon after, Taylor became a consultant to Henry Ford who in the early 1900s started measuring the time each component of his Ford Model T took to complete on his assembly line. His work and his success changed the manufacturing industry worldwide. Yet, a pen and paper was still used for that.

With the invention of electronic computers in 1930’s up until the 1950s, computers relied mostly on punch cards or punched tapes to store data. These were huge piles of cards with tiny holes in them, which would store the information to be processed by the computers. In 1956, however, IBM invented the first hard disk drive, making it possible to store large amounts of information with greater flexibility of access.

Computer use dramatically increased over the next decade, even though computers were a huge machine which covered the entire floor of a building and had to be managed by several high-skilled engineers to function properly. Experts again tackled the idea of using computers to extract conclusions from the data, but the main issue that they had was no there was no centralized method available to bring together all the data in one place.

In 1968, only individuals with highly specialized skills could transform data into usable information. At this time, data from multiple sources was normally stored in silos, and research was typically presented in a fragmented, disjointed report that was open to interpretation. Edgar Codd recognized this as a problem, and published a paper in 1970, altering the way people thought about databases. His proposal of developing a “relational database model” gained tremendous popularity and was adapted worldwide. Data, by itself, could not generate any insights. To solve this challenge, the first database management systems were designed. Later, they would simply be called databases.

During the 1970’s, Edgar Codd from IBM published a paper called A Relational Model of Data for Large Shared Data Banks. It paved the road for next-generation relational databases, allowing for a much broader capacity to store and manipulate data. A decreased in the price for storage space and better databases allowed for the next generation of business intelligence solutions.

During the 90s, information distribution centre expenses declined as more contenders entered the market and more IT experts got to know the innovation. This was the time of “Business Intelligence 1.0.”

Data was now easily accessible to the corporate staff in general, not just top management. However, the problem at this point was that asking new questions was still very expensive. Once a question was “engineered,” the answer would be available quickly, but only for that question.

In 1995, Microsoft released Windows 95 the first “user-friendly” operational system—and computers became common household items. This would have a huge impact on how people produced and consumed data for the following decades. By the year 2000, business intelligence solutions were already established as a “must have” for all medium to large businesses.