Gartner defines Business intelligence (BI) 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.
It is an OK definition. I like OLAP’s definition better:
The term Business Intelligence (BI) refers to technologies, applications and practices for the collection, integration, analysis, and presentation of business information. The purpose of Business Intelligence is to support better business decision making. Essentially, Business Intelligence systems are data-driven Decision Support Systems (DSS).
Finance Online and other more revenue focused organizations go into details and lists about what constitutes Business Intelligence. For example:
- Data mining
- Online analytical processing
A break down of Business Intelligence (BI) is made at Investopedia:
Business intelligence grew out of the conviction that managers with inaccurate or incomplete information will tend, on average, to make worse decisions than if they had better information. Creators of financial models will recognize this as a “garbage in, garbage out problem.” Business intelligence is meant to solve that problem by bringing in the most current data that is ideally presented in a dashboard of quick metrics designed to support better decisions.
As you can see, Business Intelligence is both simple and complex in all the ways it should be.
I would like to suggest that:
Business intelligence (BI) is growing out of the knowledge that decision makers with selective/subjective, inaccurate, reliable, manipulated or incomplete information tend, on average, to make catastrophic decisions. This, as compared to better decisions made based on accurate, reliable, non-manipulated and complete information from multiple objective sources.
In decision making, as in Business Intelligence, the keywords are “Crap in, Crap out.” Therefore, BI’s main goal should be to reduce the challenges faced in Decision Making by bringing in the most current data – accurate, reliable, non-manipulated and complete – from multiple objective sources.
To make this data available and fathomable for decision makers, it should ideally be visualized in user friendly presentation tools chosen with great consideration for the specific decision maker’s needs and technical maturity.
To explain what I mean, I will give the example of the yearly/quarterly comparison reports for BI tools. Every new report announces the latest “best” tool in different categories.
The only message missing from the comparison report is:
Please note before you purchase this fantastic BI tool: It doesn’t matter how fantastic the GUI (Graphic User Interface) is, in BI & analytics, if the data is crap, the decision maker will not be jubilant about the GUI.
One of the lessons I have learnt working with BI is that, the frustration caused by unreliable data, overrides the pleasure of a beautiful GUI, every single time.