What Companies Lack in BI

As much as companies are talking of committing to Business Intelligence principles in their daily work, the concept of BI still seems too utopian and vague to be successfully implemented throughout an enterprise. It's probably not that the definition is vague, it's that the practical side will differ a bit depending on companies' needs.

The one thing that is more or less universal and requires the utmost attention in all cases is data quality.

Whether your data is already 'dirty' and needs to be reviewed on regular basis, or whether there is no systematic process for checking it within your company, sooner or later you realize that something about your data needs to be fixed. Some companies prefer to conduct regular automatic check ups, others choose to apply filtering techniques before the information even enters internal databases, one way or another, enough solutions already exist to help you make that first step into the world of BI and make it right.

One of BEYE bloggers recently posted his list of the top ten things BI lacks. Aside from data quality he singles out such foundational aspects of BI as the problem of structured and unstructured data, valuation techniques, Predictive Analytics / Data Mining, technology limitations, simulations, on demand analytics, etc. The the list will vary slightly from one company to another, but making one and working towards perfecting your Business Intelligence strategy through it is certailny helpful. No one can tell you how rewarding it is, you can only feel it for yourself while gradually putting "taken care of" or "implemented" next to each item from the list.