These two terms, “data-driven” and “data-centric”, are both relatively new. They are both frequently used, and they seem to get much attention nowadays. As with all new expressions their meaning can be vague.
“A Data-Centric enterprise is one where all application functionality is based on a single, simple, extensible data model.” (Dave McComb: The Data-Centric Revolution: Restoring Sanity to Enterprise Information Systems”).
We agree with this definition. It has to do with how you manage your data and information as a resource. This approach will require long term planning and wisely design of your information systems. And it is a change from the days where each application was designed from its own data model. That historically trend is named application-centric.
Data-centric is an attractive attribute of the modern enterprise architecture. It will very much affect the application architecture, but it is derived from the information architecture. Successful digitization requires a data-centric approach.
Data-driven, on the other hand, relates to how decisions are taken in the enterprise; are they based on evidence or facts, or are they taken more by guts feeling and personal preferences. An evidence or fact-based approach is called data-driven. It requires adequate data presented as meaningful information up front of decisions. Of course – if your enterprise is data-centric the data-driven approach will be much easier and less costly.
When enterprises digitize, they want to automate business processes. Decisions are taken all the way along a business process. Decisions in a business process can of course not be automated based on guts feeling. That is not possible. You will have to convert to a data-driven approach.
The two terms are not the same, but they are very much related. And they are both very actual due to all digitizing efforts. However: a successful digitizing effort requires both the data-centric approach of information systems and a data-driven mind-set of how the organisation seeks to take decisions.