I'm preparing my content for Enterprise Data World 2010, where I will speak on March 17.  My topic is "Comparison of Enterprise Data Platforms".  It's mostly based on my popular service helping get end clients into the right platforms for them.  I'm covering the DBMS market (where we've come, where we're going), data warehouse appliances, columnar data storage, open source, on-demand and virtualization.  In 1 hour! 

I'll do my best, but one thing that struck me as interesting as I reviewed was that the future of data management will have many opportunities as well as confusion in it.  Unlike about 5 years ago, the enterprise data warehouse was not only hitting stride, it was considered a "holy grail" and an end-game.  Many data management resources went into building data warehouses (with single platforms, strictly row-based structures, on standard hardware and in-house.)

This is not so true any more.  We've re-entered chaos.  A columnar orientation is working its way into enterprise architectures and popular database offerings (Microsoft, Oracle).  You need to know how it works and when to use it.  Appliances and on-demand services are pushing function out of the enterprise.  You need to know how to manage the changing roles and responsibilities.  With departmental budgets buying software-as-a-service business intelligence, low-end appliances, and open source BI tools, shops need to have integration capabilities now more than ever.  And, something I've been saying for a while, master data management is leading the charge of business intelligence back into the operational world.

The economies and performance abilities of data management are changing and the benefits need to go to your bottom line.  Most unhelpful is the terminology wars surrounding all of this.

And finally what to start doing about the MapReduce approach, and syndicated data, and the data cloud.... 

Sorry, no answers here, but sometimes it's helpful to identify the questions.