SAS Institute
Analysis of data mining powerhouse SAS, and the especially the relationship between SAS’s data mining products and various database management systems. Related subjects include:
- Statistics and predictive modeling
- Business intelligence
- (in The Monash Report) Data mining (older posts)
- (in Text Technologies) SAS’ offerings in text mining
It can be hard to analyze analytics
When vendors talk about the integration of advanced analytics into database technology, confusion tends to ensue. For example: Read more
| Categories: Aster Data, Greenplum, Netezza, Predictive modeling and advanced analytics, SAS Institute | 7 Comments |
Further thoughts on previous posts
One thing I love about DBMS 2 is the really smart comments a number of readers — that would be you guys — make. However, not all the smart comments are made in the first 5 minutes a post is up, so some readers (unless you circle back) might miss great points other readers make. Well, here are some pointers to some of what you might have missed, along with other follow-up comments to old posts while I’m at it. Read more
| Categories: About this blog, Calpont, IBM and DB2, Netezza, Oracle, SAS Institute | Leave a Comment |
Some thoughts on the announcement that IBM is buying Netezza
As you’ve probably read, IBM and Netezza announced a deal today for IBM to buy Netezza. I didn’t sit in on the conference call, but I’ve seen the reporting. Naturally, I have some quick thoughts, which I’ve broken up into several sections below:
- Clearing some underbrush.
- Speculation about what IBM/Netezza will do.
- Speculation about alternative acquirers for Netezza.
- Speculation about what IBM/Netezza competitors will do.
Various quick notes
As you might imagine, there are a lot of blog posts I’d like to write I never seem to get around to, or things I’d like to comment on that I don’t want to bother ever writing a full post about. In some cases I just tweet a comment or link and leave it at that.
And it’s not going to get any better. Next week = the oft-postponed elder care trip. Then I’m back for a short week. Then I’m off on my quarterly visit to the SF area. Soon thereafter I’ve have a lot to do in connection with Enzee Universe. And at that point another month will have gone by.
Anyhow: Read more
| Categories: Analytic technologies, Business intelligence, Data warehousing, Exadata, GIS and geospatial, Google, IBM and DB2, Netezza, Oracle, Parallelization, SAP AG, SAS Institute | 3 Comments |
Further clarifying in-database MPP SAS
My recent post about SAS’ MPP/in-database efforts was based on a discussion in a shared ride to the airport, and was correspondingly rough. SAS’ Shannon Heath was kind enough to write in with clarifications, and to allow me to post same. Read more
| Categories: Aster Data, Netezza, Parallelization, Predictive modeling and advanced analytics, SAS Institute | 3 Comments |
Clarifying the state of MPP in-database SAS
I routinely am briefed way in advance of products’ introductions. For that reason and others, it can be hard for me to keep straight what’s been officially announced, introduced for test, introduced for general availability, vaguely planned for the indefinite future, and so on. Perhaps nothing has confused me more in that regard than the SAS Institute’s multi-year effort to get SAS integrated into various MPP DBMS, specifically Teradata, Netezza Twinfin(i), and Aster Data nCluster.
However, I chatted briefly Thursday with Michelle Wilkie, who is the SAS product manager overseeing all this (and also some other stuff, like SAS running on grids without being integrated into a DBMS). As best I understood, the story is: Read more
| Categories: Aster Data, Data warehouse appliances, MapReduce, Netezza, Parallelization, Predictive modeling and advanced analytics, SAS Institute, Specific users, Teradata | 10 Comments |
Revolution Analytics seems very confused
Revolution Analytics is a relaunch of a company previously known as REvolution Computing, built around the open source R language. Last week they sent around email claiming they were a new company (false), and asking for briefings in connection with an embargo this morning. I talked to Revolution Analytics yesterday, and they told me the embargo had been moved to Thursday.* However, Revolution apparently neglected to tell the press the same thing, and there’s an article out today — quoting me, because I’d given quotes in line with the original embargo, before I’d had the briefing myself. And what’s all this botched timing about? Mainly, it seems to be for a “statement of direction” about software Revolution Analytics hasn’t actually developed yet.
*More precisely, they spoke as if the embargo had been Thursday all along.
| Categories: Investment research and trading, Parallelization, Predictive modeling and advanced analytics, Revolution Analytics, SAS Institute | 12 Comments |
TwinFin(i) – Netezza’s version of a parallel analytic platform
Much like Aster Data did in Aster 4.0 and now Aster 4.5, Netezza is announcing a general parallel big data analytic platform strategy. It is called Netezza TwinFin(i), it is a chargeable option for the Netezza TwinFin appliance, and many announced details are on the vague side, with Netezza promising more clarity at or before its Enzee Universe conference in June. At a high level, the Aster and Netezza approaches compare/contrast as follows: Read more
| Categories: Aster Data, Data warehouse appliances, Data warehousing, Hadoop, MapReduce, Netezza, Predictive modeling and advanced analytics, SAS Institute, Teradata | 9 Comments |
Aster Data nCluster 4.5
Like Vertica, Netezza, and Teradata, Aster is using this week to pre-announce a forthcoming product release, Aster Data nCluster 4.5. Aster is really hanging its identity on “Big Data Analytics” or some variant of that concept, and so the two major named parts of Aster nCluster 4.5 are:
- Aster Data Analytic Foundation, a set of analytic packages prebuilt in Aster’s SQL-MapReduce
- Aster Data Developer Express, an Eclipse-based IDE (Integrated Development Environment) for developing and testing applications built on Aster nCluster, Aster SQL-MapReduce, and Aster Data Analytic Foundation
And in other Aster news:
- Along with the development GUI in Aster nCluster 4.5, there is also a new administrative GUI.
- Aster has certified that nCluster works with Fusion I/O boards, because at least one retail industry prospect cares. However, that in no way means that arm’s-length Fusion I/O certification is Aster’s ultimate solid-state memory strategy.
- I had the wrong impression about how far Aster/SAS integration has gotten. So far, it’s just at the connector level.
Aster Data Developer Express evidently does some cool stuff, like providing some sort of parallelism testing right on your desktop. It also generates lots of stub code, saving humans from the tedium of doing that. Useful, obviously.
But mainly, I want to write about the analytic packages. Read more
| Categories: Aster Data, Data warehousing, Investment research and trading, Predictive modeling and advanced analytics, RDF and graphs, SAS Institute, Teradata | 7 Comments |
SAS on Netezza and other Netezza extensibility
I chatted with SAS CTO Keith Collins yesterday about the new SAS/Netezza in-database parallel data mining scoring offering. My impression is that this is very similar to SAS’ current Teradata support, notwithstanding SAS’ and Teradata’s apparent original intention of offering in-database modeling by now as well.
I gather this is a big performance-enhancing deal, just as it is for SPSS or Oracle’s own data mining over Oracle. However, I must confess to not yet understanding why. That is, I don’t know what’s so complicated about data mining scoring algorithms that makes hand-coding them in SQL particularly forbidding. My naive view of data mining is that you do a big regression to get a bunch of weights, and the resulting scoring algorithm is a linear combination of a few dozen variables. Evidently, that’s not quite right.
Anyhow, it turns out that SAS held off on this work until it could be done for TwinFin. That’s largely because TwinFin lets partners write code on Intel CPUs, while previously they had to write in C for Netezza’s FPGAs. I got a similar sense from at least one other Netezza partner as well.