There is no excuse for not expanding the DBA knowledge base. Automation is massivley changing DBA work. The primary goals is still data integrity and access to data, but data sets are growing which requires a extension of skills
1.NoSQL. Over the last couple of years I've seen products introduced into companies with ONLY a NoSQL option. It used to be you'd get multiple RDBMS options. How will NoSQL proceed.Will NoSQL progress into ACID? There are applications which require a key-value representation . How does the DBA deal with NoSQL?
2.InMemory - OLTP - It's in it's infancy , but with the performance improvements I've seen , it's got massive potential. I initially became interested during TechEd 2013
3.Cloud - automation,auto install, patching , template builds. Bring it on! The less of these tasks you're manually completing , the better you are at your job. How can I utilise the Cloud , particuarly template builds to make my life easier? Spending more time on value - added tasks is the way to progress.
Cloud is not answer to all our problems . Database servers are unique - security, intensive processing , statefulfulness (failure will not be tolerated)
4.Columnstore indexes - Initially when I played around with Columnstore indexes in sql server 2012 - I saw it as a non clustered index sitting on top of a table. But since 2014 - I've seen the compression \ performance benefits. I'm starting to work on various projects with Columnstore index
5.We manage data , not Servers . A change in mindset . In practical terms more knowledge on : Retention, ETL,Datawarehouses,data analytics databases as a service, reporting.
Underlying these skills are still deep technical knowledge. for example, analytics may be underpinned by modelling and the modelling requires intensive processing . Data sets are getting bigger - which introduces it's own set of technical challenges.