Enterprise Data Management Is Not The Holy Grail
From my first days as a baby architect, I was spoon-fed the idea that enterprise data management (EDM) was the solution to our data woes. Some call it enterprise information management or other names that mean a holistic approach to managing data that is business led and centered on stewardship and governance. The DMBOK provides a picture that describes this concept very well — check it out.
Here’s the problem: Most firms are not able to internalize this notion and act accordingly. There are myriad reasons why this is so, and we can all list off a bunch of them if we put our minds to it. Top of my list is that the lure of optimizing for next quarter often outweighs next year’s potential benefits.
Here’s another problem: Most EAs cannot do much about this. We are long-term, strategic people who can clearly see the benefits of EDM, which may lead us to spend a lot of time promoting the virtues of this approach. As a result, we get bloody bruises on our heads and waste time that could be spent doing more-productive things.
I do think that taking a long-term, holistic approach is the best thing to do; in my recently published report "Big Opportunities In Big Data," I encourage readers to maintain this attitude when considering data at extreme scale. We need to pursue short-term fixes as well. Let me go a step further and say that making short-term progress on nagging data management issues with solutions that take months not years is more important to our firms than being the EDM town crier. Hopefully my rationale is clear: We can be more effective this way as long as our recommendations keep the strategic in mind.
As an example, a mature technology, data virtualization, has been the subject of many reports here at Forrester and is a critical component of information-as-a-service. In my most recent report, "Data Virtualization Reaches Critical Mass," I point out that this technology can both contribute to enterprise data goals and solve immediately pressing problems.
Data virtualization has been around for about five years now, but companies are just now broadly awaking to its potential to help them operate in a world where: 1) multiple BI tools and data warehouses are a fact of life; 2) the structure and format of data produced by one application will never match the needs of a consuming application; and 3) database consolidation or ETL is too expensive, time consuming, or risky.
In conclusion, I encourage working EAs to pause and rethink the fight for EDM: Work slowly to that end, but realize that you may never win. Do not forget to look for emerging technologies, such as data virtualization, that can solve immediate problems and that have a strategic upside.