Business Intelligence Defined ... Almost

The Tragedy of “Data Mining”

I suppose before we get into how Business Intelligence (BI) is used in different organisations, I should start by defining what business intelligence actually encompasses. I think it is one of those business terms that is often confused, but it is broad enough that most people feel comfortable talking about it. Before you start to engage across the business you should have an idea of what this means for your organisation and what is understood in the BI community or we could force BI into the same situation that the term “data mining” is currently. I would say that the term “data mining” is one of the most widely misused words in the BI field. I feel that this is because people hear the word “mining” and automatically attach the real-world understanding, which is to basically dig into the ground to dig up precious “stuff”. It must mean the same in a data context right? Well... sort of. It is more than just trawling through a mess of a data warehouse and finding the magic number you were looking for, it extends to identifying trends in the data by way of clustering, regression, classification and other relationships...this is more than simply finding a data point!

Back to the task at hand of defining Business Intelligence, one way to help with a definition is to start with what it is not. It is not a data warehouse, data mart or any other large store of information. This is certainly part of a BI framework the same way a wheel on a car is a part, and not the whole. A data warehouse gets BI moving, but on its own it is certainly not the final solution to most organisations challenges of access to information. I have been in meetings with customers stating that their BI woes had been resolved with an investment in a data warehouse. Relational data is great, but these companies will lose any competitive advantage they have if this investment is not leveraged.

Where Was BI Born?

A good place to start with the definition of BI can is in its traditional nomenclature as a Decision Support System (DSS) for the business. This definition has its grass-roots at MIT and Carnegie Institute in the 60’s. A DSS is differentiated in that it is a computer-based information (and knowledge-based) system that supports decision making activities rather than relying wholly on gut-feel and paper-based models of yesteryear (although these are still important aspects of decision making today). If we take this to the next level of detail, what we are talking about is information that we receive from our computer-based systems that assists in decision-making that may take the form of reports, alerts, portals, OLAP cubes, data warehouses/marts, and results from analytics (statistical and other). The information presented for decision making encompasses historical, present and predictive views and is customised by role – no matter where they sit in the organisation.

It’s Up To You

Ultimately BI should provide you with an intimate, interactive experience for developing a relationship with your data – no matter where it sits (internally and externally), but the reality is that you are responsible for defining what your organisation needs recognising that the solutions are there to unlock your information for decision making. To find out more on how your organisation can unlock your information, contact me for a workshop: Jason.Gates@Oracle.com