The logical data warehouse is already creating a stir in the traditional data warehouse market space. Less than 5% of clients with implemented warehouses that we speak with are pursuing three or more of the six aspects of a logical warehouse: 

• repositories
• data virtualization
• distributed processes
• active auditing and optimization
• service level negotiation
• ontological and taxonomic metadata

That means we are in a very early stage regarding the adoption trend, and vendors who are aggressively moving toward it are ahead of their customers.

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My name is Mark Beyer, and I am the “father of the logical data warehouse”. So, what does that mean? First,  if like any father, you are not willing to address your ancestry with full candor you will lose your place in the universe and wither away without making a meaningful contribution. As an implementer in the field, I was a student and practitioner of both Inmon and Kimball. I learned as much or more from my clients and my colleagues during multiple implementations as I did from studying any methodology. My Gartner colleagues challenged my concepts and helped hammer them into a comprehensive and complete concept. Simply put, I was willing to consider DNA contributions from anyone and anywhere, but through a form of unnatural selection, persisted in choosing to include the good genes and actively removing the undesirable elements.

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As demonstrated in movie “Moneyball”, starring Brad Pitt and opening in theaters today (http://www.moneyball-movie.com/), professional sports teams are increasingly using data mining and statistical analysis to find the players that best correlate to success.

 This approach has resulted in the displacement of many long-held, but less relevant, performance statistics and “gut feel” recruiting approaches. Many successful teams are building on – and supplementing – this fact-based approach to winning by using collaborative decision making (CDM) platforms that enable key team decision makers to assess, weight and optimize a combination of quantitative and qualitative measures used to select the best players at any one time to meet their specific team needs.

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While we’re talking about kids – ever watch young kids play soccer? Everyone surrounds the ball. It takes years to learn their position on the field and play accordingly. There are emerging alphas, a few stragglers on the sidelines hoping for a chance to play, community participants – and a clear need for governance. Tech markets can be like that, and with 1600 attendees packing late June’s Hadoop Summit event, all of those scenarios were playing out. Leaders, new entrants, and the big silents, like the absent Oracle and Microsoft.

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Feel free to go there and check it out. You don’t have to be a Gartner client. My next task will be figuring out what to do here, and what to do there – if they don’t turn out to be fundamentally the same thing…

familiar with the concept of drafting – travelling close behind another vehicle to reduce wind resistance. The concept is sometimes applied to marketing by savvy practitioners who use the spend of others to multiply their own impact in public consciousness. In recent months, I’ve noticed a growing use of twitter by companies – including research firms – to exploit the new social channel this way.

It’s not new. Back in the days when Comdex was the biggest, most interesting show in IT, one could sometimes find the most intriguing offerings, especially from small firms with correspondingly small budgets, in hotel rooms nearby. Rather than paying the sizable fees required to participate officially, these nimble players bypassed the show entirely and found ways to reach attendees and draw them to parties, chili cook offs, etc. to get their message across.

The age of twitter, and especially hashtags, has created a new opportunity. If you don’t know what a hashtag is, they are words preceded by the # sign, a convention that allows an event – like #IBMPulse or #OracleOpenWorld – to sustain what is known as a tweetstream of messages the community interested in the event can follow. (Hashtags are used for other topics too, but that’s not relevant here.)

How does the crafty practitioner use hashtags to get an extra kick for his or her message? By putting out their own tweets and using someone else’s hashtag. Examples: tweeting about your competing product during a vendor show, or in a tweetstream that has sprung up around an event like a product intro or news story.

Analysts can jump into a tweetstream to promote their own work inside the stream around a vendor’s show. I’ve done that myself – it’s a great way to find new followers.

Some have gone further still – lately I’ve seen twitter-savvy analysts like Ray Wang promote their firm’s work even inside a competitor firm’s event tweetstream.  It’s a great way to find the right audience at the right time, and another powerful example of how twitter and other social media challenge existing business models.

Update: in the day following this post, I observed two more instances at the Gartner MDM event I was attending. Another independent analyst used the hashtag to add commentary – on the mix of attendees of the event, which he was not present for. And a vendor, not sponsoring, retweeted something I said, adding a link to their own website. What’s your opinion of these tactics? Leave your comments below – I hope to have a lively discussion. 

Adkins’ messages focused on gaining market momentum with increased offering differentiation, targeting new workloads and clients, and driving sales and marketing execution. He made a strong case for having done well on all counts. After a difficult 2009, STG has just turned in its best Q3 performance in 6 years following gains in the prior two, and is expecting continued success to round out the year. Adkins intends to grow from 2009′s $1.3B in pre-tax income to $2B in 2015.

Every IBM hardware platform – z, POWER, x and storage – has been refreshed in 2010, with an eye to driving the differentiation Adkins spoke of. “Smart Analytics workload revenue” through September is 4x its first year total, he said, with POWER solutions and associated storage leading the way. For this observer, though, IBM doesn’t have nearly the mindshare it should in the analytic platform and data warehouse markets. It will need to step up the message volume to break out of its existing customer base and drive new business momentum. Attractive as they sound, IBM’s incremental moves to drive ecosystem performance need to be matched by a commitment to raise customer awareness.

IBM’s platform portfolio permits multiple paths to market, and some of the successes are striking. Though a few observers assert reductions in the numbers of mainframe customers, IBM focuses on its new ones: 37 new System z clients this year through September. And the transformation of the mainframe into what IBM calls “the industry’s first multi-architecture platform” could change the perception of the mainframe substantially. IBM’s zEnterprise can have POWER and x blades plugged right in, to run the workloads they are best suited or already being used for, to powerful effect. Has that message been heard in the market? Not in my opinion – again, there is a shortage of product messaging to supplement the admittedly effective Smarter Planet corporate story.

IBM boasts 4500 competitive displacements since 2006, when it began its Migration Factory initiative. On the high end, the news continues to be good: 532 wins from Oracle/Sun and 481 from HP so far this year. POWER systems continue to be a bright spot, with 800 migrations to it through September 2010, already 200 ahead of the 2009 total. On the low end, work has been done developing differentiated x platforms, and with improved revenue results in every quarter, that story seems to be taking hold as well, though it doesn’t get the laser view of wins that the lower volume, higher-priced platforms can.

IBM is using its weight as a global organization effectively in new markets: 29% of STG revenue comes from growth markets and in particular, the BRIC countries (Brazil, Russia, India and China) contribute 14% (they were up 27% year over year.) Adkins detailed the opportunity IBM sees: $650B in its key thrusts at growth markets, analytics, cloud and Smarter Planet. He concluded with a look at new growth areas like data center networking and virtualization and a discussion of go-to-market initiatives such as continuing expansion of the partner ecosystem.

Steve Mills showed his customary command of his topics. He began with a focus on workload optimized systems and observed that after 37 years at IBM, “I manage 35,000 programmers and I know what they want: ‘my own machine.’” His favorite analogy, the golf clubs that permit golfers to use the right hardware for the problem at hand, led to the observation that the extreme challenges in fabrication today demand that systems design be tightly coupled based on users’ requirements.

Mills customarily focuses on the economic issues, and this presentation was no exception. He reminded his audience that labor and energy costs are bigger drivers than the machines themselves and that the billions of programs running in the world today are priceless, irreplaceable assets. He echoed Adkins’ mention of the capability to put x and POWER blades in zEnterprise with common console and workload management, noting that this supports “multi-tier loads. This compresses the environment, and delivers higher value,” he asserted.

Mills spent a good deal of time on pointing out the interconnectedness of the whole computing stack, from chip to programmer. He noted compiler investment as a key to exploiting hardware advances and the synergy implicit in having the software team and the hardware team defining requirements together. “I need the system to do the parallelism for me, not the programmer – all the way down to compiler level,” he noted. He also honed in on the appliance message as an almost inevitable result of effective software-hardware design integration; if a specific workload or function is the object of a design, the result is quite appliance-like. He cited IBM’s DataPower boxes as an example.

Still, workload-optimized systems are not all appliances. A rich system designed for many uses, however similar, like the Smart Analytic Systems, take a lot of work – they are configurable, but sophisticated artifacts created in house take time. He doesn’t mind the Oracle comparisons, though: “It takes 4-6 weeks to install Exadata. It generates lots of heat – you have to reroute your air conditioning.” He’s confident that IBM will continue to succeed in the face of the new Oracle hardware-plus-software organization, not least because of its ability to offer both configurability and appliance forms. Netezza, the new acquisition, is not designed for high degrees of configurability, but for immediate results. One can see the nascent positioning emerging. Mills replied to my Netezza question with the revelation that IBM found only a 5% overlap with existing Netezza purchasers – “We see it as a different use case. They broke the code on the data mart play,” he said.

Feistiness regarding Oracle is nothing new for Mills, and he was in fine form, pointing out the success IBM is achieving, after all, “100% of the DB2 installed base has resulted from competitive wins since 1993 – mostly from Oracle.” And “We all know that SPARC is dead. It can’t keep up” with the fabrication challenges IBM has thrown down. IBM continues to allow configurability across various parts of the stack, because “I’ve never met a customer that was interested in giving a vendor pricing power.” And that posture plays well to the proliferation of data outside IBM’s DBMSs, competitor-owned or not: “Our strategy for the last 15 years has been a federated one; people keep much of their data outside DBMSs. Our message is not to worship at the temple of [Oracle or anything else.]“

Disclosures: IBM and Oracle are clients of IT Market Strategy.

Informatica has been on a roll, upping its Data Quality game, acquiring and integrating Siperian for Master Data Management (MDM), 29West for streaming data at low latency, and, with Informatica Cloud 9, delivering a multi-tenant platform-as-a-service for data integration, as well as Amazon EC2 support. Informatica’s Q3 2010 results continued a record of 30 consecutive quarters of year-over-year growth. Total revenues grew 31% to $161 million; new license revenues were up 40% to $70 million. Analyst reports continue to acknowledge the success of its strategy to unify data integration-related product categories into a comprehensive set of offerings.

Informatica’s opportunity is huge here: bringing the kinds of tools it provides for structured data to the “extreme data” world is the next step for the pioneering user companies. The huge volumes of new information coming from web consumer applications, newly instrumented physical assets, mobile devices and more are typically being processed with new tools and new languages, outside conventional enterprise methods and teams. They contain priceless opportunities for new combinatorial approaches that will deliver new insight, new processes, and entirely new businesses. As one example, consider the kind of intensely computational scoring of customer data that firms are moving into massively parallel farms running Mapreduce over HDFS. Now think about how the profile of an (anonymous but describable) customer in Hadoop could be related to a self-described customer in CRM to enable real-time cross-selling and you see the place the two worlds overlap.

How to build the workflow needed to put this together? One way would be to take mappings designed in Informatica, convert them into MR and user defined functions (UDFs), and execute them on Hadoop. That’s one of the deliverables the two companies promise out of their partnership. The connections will be made via a scalable connector to HDFS, leveraging Sqoop in a fashion not unlike the one I described in covering the Cloudera-Membase deal, or the work Cloudera has done with Vertica, Teradata and others.

Informatica brings a far broader value proposition to the table beyond task execution. Data governance, metadata management, and administration for “outside” data are generally absent in most of the shops that are using that data more and more. Enabling reuse, providing manageability and reliability will become more important as the uses of outside data proliferate. Informatica has already demonstrated it can provide huge value to the enterprise data management function without actually being a database player. Perhaps it should consider whether partnership or ownership is the best model here.

Disclosures: neither Cloudera nor Informatica is a client of IT Market Strategy