A Who’s-Who of BI Twitterers
I noted recently that there’s an active BI community on Twitter. It turns out that Shawn Rogers is attempting to keep a master list of BI Twitterers. If you want to plug into the discussion, that’s a good list of URLs to start with.
| Categories: Business intelligence | Leave a Comment |
SAP slashed 1000 VP-level employees?
The late Art Buchwald, when giving talks at conventions, used to start by expressing his pleasure at the opportunity to see “thousands and thousands of vice presidents.” Well, according to a Seeking Alpha blog post,
SAP cut 1,000 VP-level employees in North America in 2008, and has plenty of room for additional cuts.
As Dave Kellogg points out, that would be 2% of SAP’s entire work force, all in laid-off VPs or VP-equivalents. That doesn’t seem right to me. At least in the parts of SAP’s organization I used to deal with, SAP didn’t seem particularly VP-heavy. Even with the grade inflation commonly represented on salespeople’s business cards, I’d be surprised to learn SAP had 1,000 VPs total, let alone 1,000 spare ones to lay off.
| Categories: SAP AG | Leave a Comment |
Kickfire reports a few customer wins
Kickfire has the kind of blog I emphatically advise my clients to publish even when they don’t have management bandwidth to do something “sexier.” If nothing else, at least they record their customer wins when they can.
The current list of cited customers is two application appliance OEM vendors (unnamed, but with some detail), plus one Web 2.0 company (ditto). They’ve also posted about a Sun partnership.
| Categories: Data warehouse appliances, Data warehousing, Kickfire, Market share and customer counts | 1 Comment |
Intelligent Enterprise’s Editors’/Editor’s Choice list
I have a blog on Intelligent Enterprise, which actually amounts to editor Doug Henschen’s selections of a few posts a month from DBMS2 (I still haven’t persuaded him to take anything from Text Technologies). Accordingly, I was asked to contribute thoughts this year for his annual article Editors’ Choice article. It’s out now, and as usual is a good piece. Read more
| Categories: Analytic technologies, Business intelligence, Data warehousing | 2 Comments |
Database SaaS gains a little visibility
Way back in the 1970s, a huge fraction of analytic database management was done via timesharing, specifically in connection with the RAMIS and FOCUS business-intelligence-precursor fourth-generation languages. (Both were written by Gerry Cohen, who built his company Information Builders around the latter one.) The market for remoting-computing business intelligence has never wholly gone away since. Indeed, it’s being revived now, via everything from the analytics part of Salesforce.com to the service category I call data mart outsourcing.
Less successful to date are efforts in the area of pure database software-as-a-service. It seems that if somebody is going for SaaS anyway, they usually want a more complete, integrated offering. The most noteworthy exceptions I can think of to this general rule are Kognitio and Vertica, and they only have a handful of database SaaS customers each. To wit: Read more
Gartner’s 2008 data warehouse database management system Magic Quadrant is out
February, 2011 edit: I’ve now commented on Gartner’s 2010 Data Warehouse Database Management System Magic Quadrant as well.
Gartner’s annual Magic Quadrant for data warehouse DBMS is out. Thankfully, vendors don’t seem to be taking it as seriously as usual, so I didn’t immediately hear about it. (I finally noticed it in a Greenplum pay-per-click ad.) Links to Gartner MQs tend to come and go, but as of now here are two working links to the 2008 Gartner Data Warehouse Database Management System MQ. My posts on the 2007 and 2006 MQs have also been updated with working links. Read more
Some reasons business intelligence is in a funk
I wrote recently that BI is in a “funk”. Let me now offer a few ideas as to why that is so. Read more
| Categories: Analytic technologies, Business intelligence | 1 Comment |
The business intelligence funk
Gartner analyst Andreas Bitterer’s rarely-updated blog has gotten some recent attention because of his kerfuffle with Yves de Montcheuil of Talend. Reading same, I went on to notice another post by Andreas that captured my own feelings, to wit:
Sure, the BI market has enjoyed consistent growth, has seen a lot of action on the M&A front, technology has advanced significantly (I remember when gigabytes were considered wild), and yet we are still discussing same old business intelligence. I keep hearing vendors announce that the next version of their tool will be able to address that untapped market within their customer base, growing penetration beyond those 10-15% that are using BI today. I heard this 5 years ago already, but what has changed since then? Not much.
Of course, that post was probably met with considerable PR/AR outreach to the effect “I’m so glad you said that. OUR firm really IS different, and we’d love to tell you about how.”
| Categories: Business intelligence | 2 Comments |
Pervasive DataRush
I’ve made a few references to Pervasive DataRush in the past — like this one — but I’ve never gotten around to seriously writing it up. I’ll now try to make partial amends. The key points about Pervasive Datarush are:
- DataRush grew out of Pervasive Software’s ETL business, as the underpinnings for a new data transformation tool they were building.
- DataRush is a Java framework for doing parallel programming automagically.
- Unlike most modern parallelization technologies, DataRush is focused on single SMP (Symmetric MultiProcessing) boxes rather than loosely-coupled grids.
- DataRush is based on dataflow programming.
- Pervasive says that DataRush is really fast.
More details may be found at the rather rich Pervasive DataRush website, or in the following excerpt from an email by Pervasive’s Steve Hochschild: Read more
| Categories: Parallelization, Pervasive Software | 1 Comment |
Expressor pre-announces a data loading benchmark leapfrog
Expressor Software plans to blow the Vertica/Syncsort “benchmark” out of the water, to wit
What I know already is that our numbers will between 7 and 8 min to load one TB of data and will set another world record for the tpc-h benchmark.
The whole blog post has a delightful air of skepticism, e.g.:
Sometimes the mention of a join and lookup are documented but why? If the files are load ready what is there to join or lookup?
… If the files are load ready and the bulk load interface is used, what exactly is done with the DI product?
My guess… nothing.
… But what I can’t figure out is what is so complex about this test in the first place?