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Barry Devlin

As one of the founders of data warehousing back in the mid-1980s, a question I increasingly ask myself over 25 years later is: Are our prior architectural and design decisions still relevant in the light of today's business needs and technological advances? I'll pose this and related questions in this blog as I see industry announcements and changes in way businesses make decisions. I'd love to hear your answers and, indeed, questions in the same vein.

About the author >

Dr. Barry Devlin is among the foremost authorities in the world on business insight and data warehousing. He was responsible for the definition of IBM's data warehouse architecture in the mid '80s and authored the first paper on the topic in the IBM Systems Journal in 1988. He is a widely respected consultant and lecturer on this and related topics, and author of the comprehensive book Data Warehouse: From Architecture to Implementation.

Barry's interest today covers the wider field of a fully integrated business, covering informational, operational and collaborative environments and, in particular, how to present the end user with an holistic experience of the business through IT. These aims, and a growing conviction that the original data warehouse architecture struggles to meet modern business needs for near real-time business intelligence (BI) and support for big data, drove Barry’s latest book, Business unIntelligence: Insight and Innovation Beyond Analytics, now available in print and eBook editions.

Barry has worked in the IT industry for more than 30 years, mainly as a Distinguished Engineer for IBM in Dublin, Ireland. He is now founder and principal of 9sight Consulting, specializing in the human, organizational and IT implications and design of deep business insight solutions.

Editor's Note: Find more articles and resources in Barry's BeyeNETWORK Expert Channel and blog. Be sure to visit today!

As mentioned in my last post, ParAccel had a really interesting announcement coming out this week.  I was talking about their partnering with Fusion-io to attach SSD technology in their Paraccel Analytic Appliance for even faster query performance.  ParAccel are not alone in their use of SSD; Teradata's 4555 and Oracle's Exadata 2 also include the technology.  For me, it's not even about faster query results for users.  It's about the implications for the entire Data Warehouse architecture.

Over the past couple of years, we've seen dramatic improvements in database performance due to hardware and software advances such as in-memory databases, columnar storage, massively parallel processing, compression, and so on as described in my white paper from April 2009.  SSD, in one sense, is just another piece of accelerating technology.  However, add it to the existing list, and you begin to see the possibility of revisiting old assumptions about what is possible within a single database.  Here are a few ideas to play with:

  • Do you still need that Data Mart?  With so much faster performance, maybe the queries you now run in the Mart could run directly on the EDW.  Reducing data duplication has enormous benefits, on storage volumes, but principally in reducing maintenance of ETL to the Marts.
  • Where to do operational BI?  It was once considered necessary to install a separate ODS to support closer to real-time access to consolidated atomic data.  But with such a fast database, couldn't you just trickle feed the data and do it all in the Warehouse itself.  One less copy of data and one less set of ETL can't be all bad!
  • ETL or ELT?  Extract, transform and load has been the traditional way of loading a Warehouse, with a special engine to do the transform step.  Well, with a faster and more powerful database engine, you have the option to try extract, load and transform and let the Warehouse database do the transform work.
Although ParAccel, like all the smaller vendors are focusing more on selling to the "bigger, faster, more complex analytics applications" market at present, I'm pretty sure that the work ParAccel is doing under the covers on query optimization, workload management, loading and updating features will pave the way for a sea change in how we do data warehousing in the next few years.


Posted February 17, 2010 2:34 PM
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