IBM’s new private cloud environment for business analytics could be considered the culmination of IBM’s overall strategy around analytics to this point.
On 16 November, IBM announced its private cloud computing environment for business analytics, which launches internally with more than a petabyte of information, equivalent to 20 million four-drawer filing cabinets filled with text, which stacked end-to-end would circle the entire planet Earth. And to share the success models of this internal project, IBM also announced a new solution for clients to build their own private cloud environments based on this architecture, called IBM Smart Analytics Cloud.
IBM Smart Analytics Cloud provides easily consumable business intelligence services, systems and software to help customers create an efficient delivery of shared business intelligence services across lines of business and functional organizations, IBM officials said. IBM’s own Analytics Cloud deployment served as the template for this solution offering, which features:
Some IBMers my cringe at the use of the word “culmination” to describe what the cloud analytics play means for the company’s analytics push, because there is so much more that IBM plans to do in this space.
“‘Culmination’ makes it sound like there’s nothing more…there will be more around this in the first half of next year. That said, this is certainly the result of many recent acquisitions,” an IBM spokesperson said.
Indeed, IBM’s acquisitions of companies such as Cognos, RedPill Solutions and SPSS, among several others have strengthened the IBM business analytics portfolio, but the company is not done yet. IBM intends to continue to seek dominance in this fast growing market segment through both acquisitions and internal growth, Big Blue officials said.
Ambuj Goyal, general manager, Business Analytics and Process Optimization, IBM Software Group, said, “This is a trend for us. This is not just an announcement; it’s a journey for us.”
Goyal, who has shepherded the business intelligence and analytics acquisitions for IBM, said, “This is an example of how IBM’s $6 billion worth of R&D is coming together to further the company’s overall mission. We will continue to grow through both organic moves and acquisitions.”
For instance, SPSS had been a global leader in predictive analysis with 20 years of experience before it became part of IBM, Goyal said. IBM now owns all of that expertise.
Dave Laverty, vice president of worldwide information management marketing at IBM, said IBM has expended its efforts across the company to “help clients accelerate information-led transformation. Laverty said IBM has made more than $10 billion in investments in information management software, and has more than 4,000 global business service analytics consultants.
Overall, the amount of time, effort, manpower and financial investment IBM is putting into analytics is impressive, Goyal said. And IBM Research deserves credit as well for enabling Big Blue to push its analytics offering into the cloud, company officials said.
Steve Mills, senior vice president and group executive of IBM Software group, said, “Our clients’ investment in business optimization projects is growing more than twice as fast as business automation.” Analytics play a key role in IBM’s business optimization efforts.
Mils said he has noticed three trends that IBM is addressing: workload optimized computing; workload optimized systems; and simplified, unified infrastructure. Moreover, he said characteristics of analytics workloads include search and query, predictive analytics, and risk analysis.
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In addition to IBM?s broad analytics initiative, there are various options to leverage predictive analytics using a cloud infrastructure. One example is the open standards based ADAPA scoring engine from Zementis, available as SaaS on the Amazon EC2 cloud. See http://www.zementis.com for more information.
Also of interest in this context is the Predictive Model Markup Language (PMML ? http://www.dmg.org ) as the de-facto standard for data mining models. Supported by all major vendors and open source tools, it bridges facilitates the deployment and real-time execution of predictive models in operational environments. Please feel free to join our active discussion group for PMML on LinkedIn.
Predictive Model Markup Language (PMML) group:
http://www.linkedin.com/groupRegistration?gid=2328634