This is my first blogpost, cross-posted from LinkedIn where I posted this on Dec 23,2015.
As we are reaching the end of another (Big Data :)) year I conclude the following:
1) Gartner removed 'Big Data' from the Hype cycle (Hurray!) and replaced it with more differentiated / practical hypes-to-come (Oh my...)
http://www.theregister.co.uk/2015/08/21/forget_big_data_hype_says_gartner_as_it_cans_its_hype_cycle/
2) Unfortunately, there is still a lot of 'Big Data' hyping going on. Just scrolling through my LinkedIn / twitter feeds show this every day...
3) When I am examining these stories they largely boil down to 'selling data and its derived usage (information, knowledge, wisdom)' under a 'let us call it Big Data now' flag...
4) The stories about real Big Data 'discoveries' going to production are still quite minimal...
So, to battle these issues, these are my professional good intentions, working for the great company DIKW in DWH / BI architecture roles:
1) To keep on advocating for a re-invented form of the (integrated) EDW: it can be an enabler for REPEATABLE data science discoveries (the move to production)! Just develop/build them in a more modern/agile way using ETL automation / metadata driven (semantics/rdf) , using data virtualisation when possible...
2) In addition to the first point: I will keep on telling good conceptual / logical data modelling is even more necessary than before. From the 'Data Lake' to 'Whatever self service BI tool you bought THIS week'... And then, in the last stage of the modelling process (the physical implementation of the data model) use more data virtualization / schema-on-read technology.
3) To keep on focusing on Data Management and Data governance, for instance using Ronald Damhof his Data Quadrant Model:
http://prudenza.typepad.com/dwh/2015/06/make-data-management-a-live-issue-for-discussion-throughout-the-organization.html
These are my 'Good Data' Intentions for 2016!
What are your #Gooddataintentions2016?
