Metadata seems to be on mind quite a bit lately. Maybe it’s because I am working on several metadata initiatives at work. When I look back over my career, metadata has always been part of my job but not the primary focus. Let me clarify that last statement. For over twenty years, I have held a variety of data oriented positions. The primary focus has always been to deliver data models to the enterprise. Metadata was always there in a supporting role.
My personal observation is that metadata has been steadily gaining acceptance and recognition over the years. When I began modeling in the late 80s, metadata had a limited scope. It was the definitions and characteristics of data models and database tables. For most people, it was the IBM file layout of a VSAM file. It was nice to have but was found mostly in binders and documentation that was shelfware.
Data warehousing raised the consciousness of metadata’s role in the enterprise. The term became more main stream. Unfortunately, most data warehouse projects did not focus on managing metadata and saw it as an optional exercise that was often left to the end of a project where the budget and sponsor support waned. No one could really quantify its value in dollars and cents. Alas, still the ugly stepsister.
Fifteen years have passed since I began modeling data warehouses. Metadata management in the BI development environment has progressed considerably. As I mentioned in a prior post, with this progression came some but not complete integration. It’s possible to trace lineage to some extent but the holy grail of end-to end, source-to-target mapping in a complex enterprise is still many years away. What has happened is that our projects have picked the low hanging metadata fruit and left the more complex solutions on the tree unpicked. Integration is still just too hard to do.
In 2011, I find that the interest in metadata has expanded past the database folks. Thought for the longest time as the domain of the “data group”, it has come into its own in software development, infrastructure and IT management groups. How and why did this happen? Without a doubt the explosion of technology solutions and complexity of integration drives the need. The work of data administrators years ago did not go in vain. IT as a whole recognized how it benefited the data group and knew that metadata could hold the same promise for them.
It would be nice to say that IT and corporate management recognized the value of the data group’s relentless sales pitch over the years for metadata management. I realize that it is more about a more universal need for metadata from all IT work groups. In a tight economy, profitability is high on the minds of management. Improving work group efficiency, process integration and workgroup cooperation can make good progress in improving the bottom line. Metadata management is key in making that happen.
That brings me to where I am today. Although I still am a data modeler, I now spend more time with metadata. I find myself being asked to lead or serve a major role in metadata initiatives. As a data professional, it’s a natural match. Who else in an enterprise has spent more time working with metadata than the data team?
What does it mean for you? Well, you now have the opportunity to step outside that pigeon holed role as the person who creates the data model into an expanded role where you model and integrate your metadata. You become the leader, the resident expert on metadata, and the pioneer who leads the way. What you will see is that with this larger team interest in metadata is the benefit of advancing your deployment of metadata to the enterprise. My core belief is that success as a data professional is highly dependent on your communication and work group collaboration skills.
I’ve reached 2NF in “Why Be Normal?” How normalized are you?
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