PASS 2015 has kicked off in Seattle, well the precon’s have anyway on Mon & Tue. The actual conference starts on Wed-Fri!
I attended a precon session today called Optimize “All Data” with a Modern Data Warehouse Solution held by Bradley Ball and Josh Luedeman of Pragmatic Works.
The session had a focus on moderising the corporate data warehouse via focusing on Data Lifecycle Optimisation.
What does that mean?
Well – It means focusing on a define set of critical technology and business areas around the corporate data warehouse and strategically implementing a managed approach to improving the corporate data warehouse via introduction of technologies and processes. Specifically this looked at 6 areas around the corporate data warehouse to consider in your approach to modernisation;
- Architecture and Configuration
- Availability and Continuity
- Maintenance and Optimisation
- Enterprise BI
- Big Data Architecture and Deployment
- Business and Predictive Analytics
Key Takeaways
Yes, so I am not going to repeat it all here, though I can say that the guys were pretty detailed in each of the 6 areas they recommended to consider – however I had a few interesting (non-scientific!) takeaways that I thought were good to note;
- The guys ran a number of unscientific straw-polls of the room (of 200 tech professionals from a variety of industries) – I recorded the interesting ones (to me anyway) that were around cloud, analytics and big data;
- 25% are using cloud now, 25% are looking at it
- 5% will never look at cloud due to regulatory reasons (which is interesting given the “street cred” Azure Public Cloud has? – https://azure.microsoft.com/en-us/support/trust-center/compliance/)
- 10% actively document their DW platform – I assume 90% don’t. That’s a lot!
- 10% actively implement an approach to data governance – so I assume 90% either don’t know what it is, don’t have the know-how or simply feel they don’t need it. I can see this really changing over time as the data warehouse becomes larger, more complex and brings in more data from a variety of private and public data sources (both trusted and untrusted). Without tracking data back to an underlying “System of Record (SoR)” then there is no guarantee that the business will have trust in the data. This in my view continues to put emphasis on the evolving role of the so called Data Steward.
- 90% dont have a big data strategy or any implementation (yet) – or probably saying it differently, they dont have a business problem yet (that they know of) that needs a technology approach to big data
- And yet 75% have had the business ask for a big data solution without really knowing what problem they have which they feel needs big data to solve!
- 50% know or have heard of R, but only 5% have developed analytic solutions with it.
- 50% of the room had NetFlix 🙂
- The corporate Datawahouse will continue to survive and even thrive – and be the source of targeted, high value, well structured and (hopefully) well documented corporate data sets. An example being your POS transnational data.
- Big data solutions will continue to rise and become more prevalent over time, but will (in many cases) have a requirement to integrate aggregated subsets of data either into or alongside the corporate data warehouse though tools like Polybase (SQL 2016 & APS). An example being weblog data tracking customer traffic on an online corporate store front.
Overall good session which shows that the Corporate Datawarehouse is definately not dead – or dying – anytime soon and that new technologies like Big Data and Analytics (Machine Learning) do sit/fit quite nicely right alongside the rich and structured data that is the DW.
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Filed under: Azure Machine Learning (ML), Big Data, Data Warehousing, PASS, SQL Server 
