One of the most heard buzz words in the world of Business Intelligence these days is analytics. As different vendors use this term differently (of course to their own advantage 
) it is important to give some sort of definition before I continue this post. Therefore I would like to refer to a quote of Thomas Davenport “I think of analytics as a subset of BI based on statistics, prediction and optimization.” Using this definition it is easy to conclude analytics is not the same as reporting, dashboarding or even OLAP. Yes these techniques can be used to present the reults of analytics, but they are not analytics themselves. In my view analytics is more like an engine applying data mining and predictive algorithms to the data in order to enable things like sales forecasts, customer segmentation, fraud detection, revenue prediction and cash flow optimization.
From a technical point of view an analytical model is like an ETL mapping that adds “intelligence” to the raw data. from a functional point of view analytics enables organisations to define an answer on question like “why is this happening?”, “what will happen (if this trend continues)?” and even “what should we do to make it happen?” whereas traditional BI solutions only focus on what has and is currently happening.
Where in the past analytics were only used in the world of science, the usage spreads. That is no wonder if you take into account the heavilly growing amounts of data that can be used to base decisions on. And of course there are obstacles that need to be taken before an organizating can fully take advantage of analytics. High quality data, or a good insight in the quality of the data is needed before applying analytics. And form a business point of view a change in management culture from “common business sense” to fact based decisioning, relying on analytics, is needed to optimally take advantage. And although this is not something that can be achieved in months, the return on investment can be enormous if it enables organisations to “sense” and “anticipate”. That given, it is no wonder why SAS reports a 26% growth in income related to business analytics. It is also no wonder why IBM bought SPSS and heavily invests in this area. Analytics is getting big!
