May 7, 2010
Notes and cautions about new analytic technology
As previously noted, I headlined Aster’s Big Data Summit in Washington, DC last Thursday. More than others, that talk did reuse material I’d presented before. I promised the audience that when I got back I’d put up a blog post linking to supporting material for the talk.
Part of the time, I talked about things I’ve written about before. For example:
- Liberty and privacy. That’s a link to my most recent overview post on the liberty and privacy implications of modern analytic technology. The notes I spoke from were actually posted previously, after I spoke from them at the New England Database Summit at MIT in January. I’m gratified that, at both events, I got very positive feedback on liberty and privacy issues.
- Pick the right latency. That’s a link to a post (also based on a previous talk, in this case the one I traveled around the world giving for Netezza last September) in which I laid out the different levels of speed and latency an analytic application might require. I counted 9 orders of magnitude between the slowest and fastest, which is pretty much the difference between the speed of a turtle (at least a small, slow one) and the speed of light.
- On the more general point of operationalizing analytics, my best or at least most detailed writing to date may be in a 2004 whitepaper on analytic business processes which, sadly, is still fairly futuristic today.
- I offered a few ways to think about the different kinds of data that go into data warehouses.
- Some of those were outlined in a post last January about three broad categories of data, distinguishing among human/tabular, human/non-tabular, and machine-generateddata.
- That was a kind of sequel to a post last December about a three broad categories of data warehouse house growth drivers, namely more of the same vs. more detail vs. wholly new kinds of data.
- I gave some examples of creating new data to analyze back in 2005 and 2006.
- Comments I made at various points were foreshadowed in a post on reinventing business intelligence.
I also raised a few points that I’m not finding good links for. I’ll try to cover those in future blog posts.
Related link
- Notes for my Boston Big Data Summit (no relation to Aster Data’s Big Data Summit series) talk in October, 2009
Categories: Aster Data, Business intelligence, Data warehousing, Predictive modeling and advanced analytics, Presentations
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