Business Intelligence tools is a term that has become commonplace within the analytics community, with a definition that has been slowly refined through the years. Today, Gartner defines Business Intelligence as “an umbrella term that includes the applications, infrastructure and tools, and best practices that enable access to and analysis of information to improve and optimize decisions and performance.”With such a broad definition, it is easy to get lost in the meaning and purpose of the term, especially as Business Intelligence tools vary so much in terms of functionality. To get a better understanding, let’s take a look at what the term meant decades years ago.
Business Intelligence “Tools” in the Beginning
The term “Business Intelligence” dates back to the 1860s when it appeared in R.M. Devens’ Cyclopædia of Commercial and Business Anecdotes. Devens describes a network of informants that worked as data collectors, helping provide him information so he could make better informed decisions. No doubt these sort of Business Intelligence networks have existed as long as competition between enterprises.
… Then Along Came the Personal Computer
It was in the 1950s, however, that Business Intelligence began to be industrialized. In 1958, an IBM researcher described Business Intelligence tools as:
“An automatic system (s) (…) to disseminate information to the various sections of any industrial, scientific or government organization. This intelligence system will utilize data-processing machines for auto-abstracting and auto-encoding of documents and for creating interest profiles for each of the “action points” in an organization. Both incoming and internally generated documents are automatically abstracted, characterized by a word pattern, and sent automatically to appropriate action points.” (Luhn. Business Intelligence System, IBM Journal, October 1958.)
Luhn, the author of the paper, called this conceptual Business Intelligence tool a “Business Intelligence System.” He lays out the exact technical requirements for an end-to-end Business Intelligence tool that would provide executives with all the data they need to make decisions.
But critically, Luhn didn’t stop there. He argued the Business Intelligence System would also generate written documents and action points, essentially explaining the results of the data collection and analysis within the system.
In short, at the advent of contemporary Business Intelligence, Natural Language Generation (NLG) was already seen as the last step in the process, the last mile in the Business Intelligence & Analytics process.
