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IBM iron predicts the future

BAO boxes combine warehousing, analytics

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Back in May, at its annual day to preach to IT and Wall Street analysts, IBM laid out is vision for providing real-time, predictive analytic systems that will allow managers to take longer lunches and take credit for ideas that are not their own.

Well, something like that.

IBM wants to take control over the business analytics and optimization (BAO) segment of the IT space, which Big Blue reckons is growing at a significantly faster pace than the traditional back-end systems which its bread and butter come from. At its May confab, it said it would deliver systems that were highly optimized for precise industries to not only do data warehousing, but also provide the aforementioned analytics.

Today, IBM trotted out the first of these specialized systems, which it calls the Smart Analytics System. It also provided a technology preview of an add-on appliance for its System z mainframes, called the Smart Analytics Optimizer, that Big Blue said will substantially speed up queries on those mainframes, thereby not severely impacting the performance of the applications and batch jobs that run on mainframes.

That the Smart Analytics machinery was previewed today, at the same time that IBM announced its $1.2bn acquisition of predictive analytics software maker SPSS, was a coincidence. But IBM needed the predictive analytics software created by SPSS to round out its BAO boxes, which had real-time information culled from data warehouses but which will now be able to predict business - presumably about as well as we now predict the weather or deals like IBM taking over SPSS, which was on no one's radar.

But forget those cynical thoughts for now.

IBM is excited about the BAO opportunity and market that it is largely defining by putting ERP, CRM, SCM, and other transaction-processing systems on one side of the data center and putting data marts, data warehousing, and analytics on the other.

The business automation space, explained Steve Mills, general manager of IBM's Software Group, accounts for about $566bn in sales - 2008 data, repeated from the analyst day event - but the growth here is about 3 per cent compounded over a few years (from 2007 through 2012, actually).

While the BAO opportunity was only about $105bn globally last year, its revenue growth is projected to be 8 per cent over the same term. What Mills did not say today, but what Frank Kern, general manager of IBM's Global Business Services group, said back in May is that within the next five years, Big Blue expects that it will get as much revenue from BAO systems as it drives with ERP systems today.

This BAO opportunity is why IBM shelled out $5bn in November 2007 to buy Cognos, why it is spending $1.2bn today to buy SPSS, and why it has spent over $10bn since 2005 buying software companies or investing in software development for database, data warehousing, and related information-management technologies.

Rather than sell general-purpose servers with a stack of operating system, database, and clustering software with layers of Cognos and SPSS software running atop that, as IBM and other system makers have been doing for years to build data warehouse and analytic systems, the Smart Analytics System will be a tightly integrated, highly optimized setup.

As Mills puts it, such tight integration and optimization is necessary to bring ease of sale and support to IBM and ease of consumption and use for end users. The only way to get orders of magnitude in performance, according to IBM's smarties, is to create hybrid server and storage setups that bring various hardware and software technologies together and sell them as a single unit.

This is increasingly how supercomputers are built and sold, and this is probably how plenty of systems will be sold. Looking ahead, Mills - who is not a systems guy - said that it would not be unreasonable to see hybrid and tuned systems like the BAO boxes account for a double-digit share of ongoing server sales. That's as good as blade servers.

The problem with giving customers highly tuned and optimized systems is that they have so many different workloads that it's hard to generalize. But there are places where IBM can generalize, and do custom integration and programming if necessary for special cases, as it does now.

Mills says that optimized systems are necessary to drive performance up and costs down, but that each industry has its own algorithms, its own data volumes and types, and its own latency requirements. "What you need to do fraud analysis for real-time banking transactions is not the same setup you need for customer loyalty applications at retailers," he warns.

IBM has committed to offer hybrid and tuned machinery for six different areas, and where appropriate, to deliver them both as complete systems - with a single product number, preconfigured and ready to go - and as cloud infrastructure that customers can rent from the IBM Cloud.

These areas include analytics, collaboration, application development and testing, virtual desktop, virtual infrastructure, and business services. Because of data security issues and the sheer volume of data in warehouses, there will not be an IBM Cloud version of this BAO box. But IBM can, and probably will, offer to run and manage a local copy of the BAO box in your own data center, but with CloudBurst cloud infrastructure.

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