January/February 2018 issue of acmqueue

The January/February issue of acmqueue is out now


  Download PDF version of this article PDF

ITEM not available


Originally published in Queue vol. 9, no. 5
see this item in the ACM Digital Library



Graham Cormode - Data Sketching
The approximate approach is often faster and more efficient.

Heinrich Hartmann - Statistics for Engineers
Applying statistical techniques to operations data

Pat Helland - Immutability Changes Everything
We need it, we can afford it, and the time is now.

R. V. Guha, Dan Brickley, Steve MacBeth - Schema.org: Evolution of Structured Data on the Web
Big data makes common schemas even more necessary.


(newest first)

Michael Hausenblas | Wed, 08 Jun 2011 10:26:25 UTC


Thanks for your follow-up and providing more insights ... now, I've started to contribute to what you call the 'new theory for data' in [1] and would love to hear back from you (maybe you find some time to comment directly on the post?) - but we can also take it off-line, if you prefer to ;)

Cheers, Michael

[1] http://webofdata.wordpress.com/2011/06/08/towards-networked-data/

Pat Helland | Sat, 04 Jun 2011 18:05:46 UTC

Dear Spinnetti,

I'm glad you found this useful. Business Intelligence efforts within SQL have always been somewhat within the world I've described. They typically are examining a copy of the active database and, hence, are an artifact of the past. In addition, some of the most interesting problems in BI come when you try to smash together stuff from disparate systems and, typically, this requires a shoehorn or two and some of the data almost fits together. So, I do agree with you that most BI can be understood better when you realize it is different than classic SQL. It is, of course, amazingly useful...

Thanks for your kind words and for your interest! - Pat

Pat Helland | Sat, 04 Jun 2011 18:00:05 UTC

Hey, Michael!

Thanks for your kind words. I really do have a ton of respect for the industry's SQL systems and agree with you that it is the constrained nature of the problem they address which empowers many of the amazing optimizations.

NoSQL is still getting its legs and, while we are seeing great progress and the ability to do things with scale and heterogeneity, I believe that this area still awaits new understandings to gain all the momentum it can have. That's why I ended the article with a plea for folks to contribute to finding new ways of formalizing data storage, access, and processing that include the stuff people are really doing in these systems. This is how progress usually happens, folks just do stuff, it has value, and then somebody helps explain it in a way that makes it easier to do it more effectively. I am looking forward to the community learning more and growing. Of course, along the way, we'll just DO stuff because we can make it work and solve our problems.

Thanks for your kindness and insightful comments on your blog. - Pat

Spinnetti | Fri, 03 Jun 2011 14:22:05 UTC

Great stuff! We are embarking on a Business Intelligence activity here at work, and this provides good insight to assist in expectation setting.

Michael Hausenblas | Sun, 29 May 2011 07:34:12 UTC


Thank you very much for this great article. I enjoyed reading it tremendously as well as it triggered some more thoughts about the topic [1] - KUTGW!

Cheers, Michael

[1] http://webofdata.wordpress.com/2011/05/29/tomorrows-problem-yesterdays-tools/

Leave this field empty

Post a Comment:

© 2018 ACM, Inc. All Rights Reserved.