Posts focused on live presentations, typically by Curt Monash.
It turns out that the slide deck I posted a couple of days ago underwent more changes than I expected. Here’s a more current version. A number of the changes arose when I thought more about how to categorize analytic business benefits; hence that blog post a few minutes ago with more detail on the same subject.
Unchanged, however, is the more technical list of six things you can do with analytic technology, taken from a blog post late last year. Also unaltered are my definitions of investigative analytics and machine-generated data.
As previously noted, I’m doing a webinar on investigative analytics on Thursday, March 10, at 2 pm Eastern time. I’ve now uploaded a late-draft slide deck for same. It’s pretty concise; the deck is in no way a substitute for the webinar itself, which I urge you to attend (or catch a recording of after-the-fact). But the slides — and in a couple of cases comments below them — may add some value to the definition of investigative analytics I recently posted.
I recently coined the phrase investigative analytics to conflate
- Statistics, data mining, machine learning, and/or predictive analytics.
- The more research-oriented aspects of business intelligence tools:
- Ad-hoc query.
- Most things done by BI-using “business analysts”
- Most things within BI called “data exploration.”
- Analogous technologies as applied to non-tabular data types such as text or graph.
This will be be basis for my part of a webcast on March 10 at 11 am Pacific/2 pm Eastern time. The other main part of the webcast will be a demo by the webcast’s joint sponsors Aster Data and Tableau Software.
Some of Aster’s verbiage in describing and titling the webinar is so hyperbolic that I do not want to give the impression of endorsing it. But I am very hopeful that the webinar itself will be interesting and informative, and will point people at least somewhat in the direction of the benefits Aster is claiming.
|Categories: Analytic technologies, Aster Data, Business intelligence, Data warehousing, Presentations, Tableau Software||3 Comments|
Netezza’s Enzee Universe conference is now almost over, and I still haven’t figured out what my gig as “conference blogger” entails. More precisely, I’m operating from our unspoken fallback plan, namely “If all else fails, do what you’d do anyway, but do more of it.” For me to live up to that, all Netezza had to do was find interesting things to write about — and as far as I’m concerned, they already did that last Thursday in spades; the five interesting meetings they set up for with users and partners on Tuesday were just gravy.
Another part of the deal was that I’d give a talk this morning at 9:30 am. And when I give talks, I like to put up posts that cover whatever material I haven’t written up before, while also offering the talk’s listeners convenient links to materials I have already covered previously at length.
|Categories: Analytic technologies, Business intelligence, Data warehousing, Netezza, Presentations||3 Comments|
Fearing that last year’s tight travel budgets would hamper attendance, Netezza – like a number of other vendors – decided to forgo a traditional user conference. Instead, it took its Enzee Universe show on the road, essentially spreading the conference across eight cities. I was asked to keynote six of the installments.
After the first one, Netezza Marketing VP Tim Young took me aside for two pieces of constructive criticism. The surprising one* was that he felt I had been INSUFFICIENTLY critical of Netezza. Since then, every other conversation we’ve had about content creation has also featured ringing reassurances that Tim truly wants independent, non-pandering work.
*The unsurprising one was that I’d rushed. Well, duh. After months of telling me I had a 1 hour slot, Netezza cut me to ½ hour a few days beforehand. And my talk had been designed to be high-speed even in the longer time slot …
As a result, I accepted a subsequent gig from Netezza that I would barely consider from most other vendors. Namely, for this year’s Enzee Universe – June 21-23, aka Monday-Wednesday of this week, at the Westin Waterfront Hotel in Boston – I would do some contemporaneous blogging. The parameters we agreed on included: Read more
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: Read more
|Categories: Aster Data, Business intelligence, Data warehousing, Predictive modeling and advanced analytics, Presentations||3 Comments|
My clients at Aster Data are putting on a sequence of conferences called “Big Data Summit(s)”, and wanted me to keynote one. I agreed to the one in Washington, DC, on May 6, on the condition that I would be allowed to start with the same liberty and privacy themes I started my New England Database Summit keynote with. Since I already knew Aster to be one of the multiple companies in this industry that is responsibly concerned about the liberty and privacy threats we’re all helping cause, I expected them to agree to that condition immediately, and indeed they did.
On a rough-draft basis, my talk concept is:
Implications of New Analytic Technology in four areas:
- Liberty & privacy
- Data acquisition & retention
- Data exploration
- Operationalized analytics
I haven’t done any work yet on the talk besides coming up with that snippet, and probably won’t until the week before I give it. Suggestions are welcome.
If anybody actually has a link to a clear discussion of legislative and regulatory data retention requirements, that would be cool. I know they’ve exploded, but I don’t have the details.
|Categories: Analytic technologies, Archiving and information preservation, Aster Data, Data warehousing, Liberty and privacy, Presentations||1 Comment|
I’ve long argued three points:
- It is inevitable* that governments and other constituencies will obtain huge amounts of information, which can be used to drastically restrict everybody’s privacy and freedom.
- To protect against this grave threat, multiple layers of defense are needed, technical and legal/regulatory/social/political alike.
- One particular layer is getting insufficient attention, namely restrictions upon the use (as opposed to the acquisition or retention) of data.
*And indeed in many ways even desirable
I surprised people by leading with the liberty/privacy subject at my New England Database Summit keynote; considerable discussion ensued, largely supportive. I hope for a similar outcome when I keynote the Aster Big Data Summit in Washington, DC in May. And I expect to do even more to advance the liberty/privacy discussion as 2010 unfolds.
Fortunately, I’m not the only only thinking or talking about these liberty/privacy issues. Read more
The last part of my New England Database Summit talk was on open issues in database and analytic technology. This was closely intertwined with the previous section, and also relied on a lot that I’ve posted here. So I’ll just put up a few notes on that part, with lots of linkage to prior discussion of the same points. Read more
|Categories: Analytic technologies, Business intelligence, Cloud computing, Data warehousing, Presentations, RDF and graphs, Software as a Service (SaaS), Solid-state memory, Theory and architecture||4 Comments|
My project for the day is blogging based on my “Database and analytic technology: State of the union” talk of a few days ago. (I called it that because of when it was given, because it mixed prescriptive and descriptive elements, and because I wanted to call attention to the fact that I cover the union of database and analytic technologies – the intersection of those two sectors is an area of particular focus, but is far from the whole of my coverage.)
One section covered recent/ongoing/near-future trends that I thought were particularly interesting, including: Read more
|Categories: Analytic technologies, Business intelligence, Data models and architecture, Data warehousing, MapReduce, Memory-centric data management, NoSQL, Parallelization, Presentations, Solid-state memory, Storage||9 Comments|