As you may know I recently updated the material in my book on business intelligence that was published in 2003 into a second edition. As I was reviewing the chapters on geographic data, data enhancement and using public data, it occurred to me that the kinds of analyses that large companies were starting to do in the early 2000s was becoming quite commonplace among medium-sized and large companies today, and that small businesses did not have to be far behind.
The technologies for data analysis have gotten somewhat better, but largely are similar in capability to what was available ten years ago. So to what can we attribute this increased level of adoption? Certainly, we can point to increased performance coupled with the general availability and lowered barriers to entry of good reporting and analytics tools as a few of the market drivers. But I would suggest that one of the more influential factors is the realization of the value of creating information products that benefit specific business objectives.
The innovation is not necessarily in the mechanics but in the people doing the analysis and the methods that use the tools and technologies. Today, graphic tools with many different types of analyses and visualizations are regularly employed by business users who bypass the traditional data warehouse route yet still enable lively displays of information driving decision-making. Predictive models are now core components of numerous database systems, and can be natively employed without having to call on programmers to develop applications with different underlying algorithms.
The end-user is much more sophisticated and is able to consider the different data sources to engineer analytical solutions cobbled together through the integration of data at the point of analysis. The result is that reporting and analytics has migrated its way around the Information Technology department and into the hands of the business users.