Decoding BI Market Share Numbers – Play Sudoku With Analysts

In a recent post I discussed Oracle’s market share in BI, based on a press-published chart taken from IDC data – showing Oracle coming in second. As often happens in such discussions, I got quite a few direct emails and twitter messages – some in no uncertain terms – about why the particular metric I chose was not sufficiently nuanced or representative of the true picture. I freely admit: that’s true. In general, market observers know Oracle is not typically placed second overall – but the picture is more complex than a single ranking. My point was, and is, that it’s too easy to slip into a “who’s on top” mentality that obscures true market dynamics. In this post, I’ll dig a bit deeper, and describe what different approaches or categorizations show us – and what they don’t. Finally I’ll talk about how much this matters – and to whom. Read more of this post

Cloud Performance Tuning and Capacity Planning – BTM Arrives

I’m delighted to feature this piece from Joe Clabby of Clabby Analytics, an independent technology research firm that focuses on systems, storage, networks, infrastructure, management and cloud computing. In this 8-page report, Joe looks at  business transaction management (BTM) — a segment of the application performance management (APM) market he believes anyone looking at cloud computing needs to know about.  It’s well worth investing the time to read this important piece of work.

What happens when a transaction is sent into a cloud for processing?  Which physical and virtual resources does it use (how do you do capacity planning in a cloud if you don’t know which resources a given transaction is using)?  What dependencies does the transaction have?  If the transaction is performing poorly, how can the fault be isolated?  If the transaction misbehaves intermittently, how can that fault be isolated?  And, how do you tune transactions in the cloud to improve performance?

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Confio Tries to Apply BI to DB Performance – Needs Work

The Boulder BI Braintrust hosted Confio this week. Confio is fairly small (25 people focusing on product development sales and support, with most other infrastructure outsourced), and privately held with angel and operating revenue funding it. The value proposition of their product, Ignite Performance Intelligence, (I’ll call it IPI from here) is to deliver information about database performance using a more BI-like interface. Prospective buyers (and today’s customers, who number in the hundreds) are DBAs and application performance specialists. Read more of this post

IBM’s BAO Initiative Will Change the Landscape, But More Is Needed

IBM Global Business Services (GBS) has added its first new service line since IBM acquired PWC and launched itself into the services business. GBS generated nearly $20B in revenue in 2008, a few hundred million more than the hardware side of IBM. Two other units, the software group and IBM Research,  have joined with GBS to create the Business Analysis and Optimization line, intended to make IBM the dominant player in advanced analytics focused on optimizing business outcomes.  GBS has pursued the capture and reusable packaging of intellectual property and methodologies in its engagements for some time, encapsulating business processes and industry requirements, standards and regulations. IBM proposes to combine those assets with software components and advanced work done in IBM Research to deliver a “predict and prescribe” approach to its customers’ business challenges.

This is a formidable array of assets, aligned into a 4000-person organization, and pursuing a carefully targeted set of competencies:

  • BI and Performance Management
  • Advanced Analytics and Optimization
  • Enterprise Information Management
  • Enterprise Content Management
  • Business Analytics and Optimization (BAO) Strategy

All the contributors bring substantial skin to the game. Ambuj Goyal, who heads the information management portfolio for IBM Software Group (SWG), has assembled an array of data management and data warehousing tools, BI, content management, and other components, and told me, “We’re harnessing everything we’ve built.” He’s been hammering on the notion of an information agenda as part of IBM’s Information on Demand strategy, and driving awareness of the need for data quality and stewardship to attack the need for executives to feel they can trust the data they get. One in three today say they don’t, even for the relatively mundane types of reporting that are commonplace.

In IBM Research, Brenda Dietrich heads a team of 150 mathematics PhDs, many of whom have been working directly with customers to build predictive models in numerous industry contexts that will underpin some of the early projects. Three key plays are in the first round: risk and fraud analytics; analytics and data optimization; and advanced customer insight, which draws upon BAO head Fred Balboni’s recent successes driving GBS business in the retail sector.

The new organization model, in typical IBM fashion, will be rolled out on a massive scale. Of course, most of the people in the organization are being “re-badged;” they aren’t new, dedicated assets just yet, but they are experienced in many facets of the problems to be tackled and are in an accelerated program designed to bring them up to speed to meet an expected demand curve that IBM believes will be very steep. I would not bet against them.

Still, this new effort is only a step on a journey the information technology industry needs to travel. “Predict and prescribe” is necessary but not sufficient to achieving true analytics-based automation, where the “prescription” is applied to operations within policy- and rules-based guidelines, reserving the delivery of guidance to decision makers for the exceptional cases. Some advanced organizations have already built such applications, and they will have a leg up. If you are among them, IT Market Strategy would like to hear your story. Please contact us – leave a comment here, or email