A remarkable number of vendors are involved in what might be called “specialized business intelligence”. Some don’t want to call it that, because they think that “BI” is old and passé’, and what they do is new and better. Still, if we define BI technology as, more or less:
- Querying data and doing simple calculations on it, and …
- … displaying it in a nice interface …
- … which also provides good capabilities for navigation,
then BI is indeed a big part of what they’re doing.
Why would vendors want to specialize their BI technology? The main reason would be to suit it for situations in which even the best general-purpose BI options aren’t good enough. The obvious scenarios are those in which the mismatch is one or both of:
- Kinds of data.
- Kinds of questions asked about the data.
For example, in no particular order: Read more
|Categories: Business intelligence, ClearStory Data, Metamarkets and Druid, PivotLink, Platfora, Splunk, StreamBase||6 Comments|
WibiData is essentially on the trajectory:
- Started with platform-ish technology.
- Selling analytic application subsystems, focused for now on personalization.
- Hopeful of selling complete analytic applications in the future.
The same, it turns out, is true of Causata.* Talking with them both the same day led me to write this post. Read more
|Categories: Hadapt, HBase, Market share and customer counts, PivotLink, Predictive modeling and advanced analytics, WibiData||4 Comments|
How flexible does business intelligence technology need to be? Should it allow fully flexible ad-hoc data analysis, or does that overwhelm users? Are they perhaps happier with simpler, more prescriptive analytic paths? My answer is a resounding “It depends”.
On the one hand, it’s clear that some users really care about business intelligence flexibility. They don’t want the “right” dimensional hierarchy, carefully worked out in advance. They don’t even want fixed drilldown paths smartly calculated on the fly, ala’ Endeca (which, after all, ultimately didn’t succeed). Rather, they want to be able to truly choose aggregations and roll-ups for themselves.
Supporting this view is the rise of in-memory business intelligence. For example:
- SAP HANA is selling in impressive quantities.
- Further, HANA and alternatives are generating a lot of buzz. For example:
- Multiple clients have asked me for help positioning their products against HANA and Exalytics.
- Kognitio’s pretense to be HANA-like is getting them some sales too.
- QlikView has had considerable success.
But why would anybody pay up for the speed of in-memory BI? Analytic RDBMS offer blazing speed for broad ranges of queries. Parameterized reports let you do drilldowns in memory. So only if you need great flexibility do you need to keep a whole analytic data set permanently in RAM.
|Categories: Business intelligence, Market share and customer counts, Memory-centric data management, PivotLink, Teradata||Leave a Comment|
- This is a list of Monash Advantage members.
- All our vendor clients are Monash Advantage members, unless …
- … we work with them primarily in their capacity as technology users. (A large fraction of our user clients happen to be SaaS vendors.)
- We do not usually disclose our user clients.
- We do not usually disclose our venture capital clients, nor those who invest in publicly-traded securities.
- Excluded from this round of disclosure is one vendor I have never written about.
- Included in this round of disclosure is one client paying for services partly in stock. All our other clients are cash-only.
For reasons explained below, I’ll group the clients geographically. Obviously, companies often have multiple locations, but this is approximately how it works from the standpoint of their interactions with me. Read more
In November I wrote two parts of a planned multi-post series on issues in analytic technology. Then I got caught up in year-end things and didn’t blog for a month. Well … Happy New Year! I’m back. Let’s survey a few BI-related topics.
Mobile business intelligence — real business value or just a snazzy demo?
I discussed some mobile BI use cases in July 2010, but I’m still not convinced the whole area is a legitimate big deal. BI has a long history of snazzy, senior-exec-pleasing demos that have little to do with substantive business value. For now, I think mobile BI is another of those; few people will gain deep analytic insights staring into their iPhones. I don’t see anything coming that’s going to change the situation soon.
BI-centric collaboration — real business value or just a snazzy demo?
I’m more optimistic about collaborative business intelligence. QlikView’s direct sharing of dashboards will, I think, be a feature competitors must and will imitate. Social media BI collaboration is still in the “mainly a demo” phase, but I think it meets a broader and deeper need than does mobile BI. Over the next few years, I expect numerous enterprises to establish strong cultures of analytic chatter (and then give frequent talks about same at industry conferences). Read more