Software vendors use so many big words and confuse customers. Our customers have often asked us to clarify – so here I go. The definitions in this article are based on research of these terms, and the collective opinion of many of our customers and prospects. Over numerous conversations with our customers and the discussions of the terminology, the clarifications always go back to the origin of the terms and then move on to change in usage. Hence this article folows that flow. I would love your feedback as it is important to help buyers understand this.

Business Reporting

Business Reporting, as the term suggests presents the data from the database in an easy to read format. This originated when business users were frustrated that all the data was locked up in databases. There was a lot of data, but no one could get access to it without calling on IT folks. Hence Business Reporting was born.

Business Intelligence

This is a fancy name for business reporting. Business intelligence (BI) is a broad category of technologies that allows for gathering, storing, accessing and analyzing data to help business users make better decisions. In a 1958 article, IBM researcher Hans Peter Luhn used the term business intelligence. He defined intelligence as: “the ability to apprehend the interrelationships of presented facts in such a way as to guide action towards a desired goal.”

In 1989 Howard Dresner (later a Gartner Group analyst) proposed Business Intelligence as an umbrella term to describe “concepts and methods to improve business decision-making by using fact-based support systems.” Then in the late 1990s the usage became widespread (Remember the Bubble!).  Then. everything with any data reporting was called Business Intelligence. So today, Business Intelligence is a glorified term for “Business Reporting”.

Data mining

Simply put, Data mining is hitting the data with all mathematical methods available to a mathematician! The data source can be almost anything – news papers articles, financial reports, sales data, medical data, … . This means that the data can have structure or can be un-structured. And the mathematical methods that can be applied can include neural networks, genetic algorithms, statistics on steroid and anything else they can think of.

One may ask – why are they doing this? What are they mining? Well, the simple answer is that they are mining the data looking for patterns; any patterns that can reveal relationships. So the methods used are varied and the kinds of data that are mined can come from a myriad of sources.

The results of data mining are lots of data! In fact - the result of Business Reporting and BI has been data overload. Now that’s the bad news. In a world of information overload, the last thing that we need is more data. We have less time today than we have ever had before. Business users do not need more data. They need quick conclusions on what the data is saying, converted into actionable tasks. Simply put – “Please tell me what to do”.

… More on the discussion of analytics to action in the next blog.