In organizations where the data warehouse has not reached full maturity, which is pretty much the bulk of them, the data warehouse still operates as a department level. This means that the data warehouse was not designed from the ground up to serve the enterprise needs, but to serve the needs of one, or a few, department within the organization. What happens with this department level focus, is that a lot of time is spent reconciling the differences in the data that the data warehouse provides to the individual departments that require it, as each of those departments may have its own definitions for the data they are expecting.
The ultimate result of the data warehouse team having to do this reconciliation on an on-going basis, is the promotion of the idea of data governance at the enterprise level. Pushing the ownership of the meanings (thus the definitions of) the data within the data warehouse, back to the organization seems like the right thing to do, and of course, it is. It is, if it’s done properly, because what we really want to do by implementing some data governance in the organization, is to implement a master data management system, which data governance is an important part of. We are saying, “We know that the data must be managed at the enterprise level, not at the department level, and we must engage the entire enterprise in the management of the data.”.
The management of “data” at an enterprise level means removing the shackles of departmental ownership of the data while still maintaining the departmental systems that manage that data. This is, by far, the trickiest part, as it deals with people, rather than just the technology and we will examine this in a later post. For now, though, we need to understand the implications of what it means to “manage data at an enterprise level”. These implications include
- restructuring the organization a little to implement enterprise data governance,
- looking at, planning for, and possibly phasing in a master data management system,
- removing some or all of the responsibility for data integration from the data warehouse (controversial, I know),
to mention but a few. We will go into more details about these and other issues in future posts as well.
Becoming more mature as an enterprise in how we deal with our data requires a shift in the way we look at, work with, and manage the data that we need to run our enterprise. It’s a lot of work, but the rewards are definitely worth it.