Big Data and Analytics: Fueling Competitive Advantage #BDA13

June 5, 2013

in Analytics, Data Mining, Decision Management, Product News

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Bob Picciano and Les Rechan came up next to discuss Big Data and Analytics: Fueling Competitive Advantage in the New Era of Smart. Five years ago IBM launched the Smarter Planet initiative. On a smarter planet, they say, everything is connected and instrumented and this is reflected in the explosion of Big Data. To drive value from this, of course, one needs to move to analytics and innovation. Six specific announcements (some of which I have covered already):

IBM sees Big Data and Big Analytics adding value at the point of impact – driving better decisions in day to day operations both in operational systems of record and newer systems of engagement.

For analytics this means descriptive analytics, predictive analytics, prescriptive analytics (Decision Management and optimization for instance) and ultimately cognitive style learning analytics.

For Big Data this means being able to consider all information from all perspectives and delivering insight to all decisions for all people in the organization (not just strategic decisions made manually but transactional decisions automated in the front line).

The stack that IBM delivers for this runs from storage and systems to big data management to analytics (including Decision Management) and ending with consulting and solutions. The intent is to weave analytics into the fabric of a business. The architecture shown below stretches from multiple data sources through various kinds of data management and analytics to deliver decision support, decision management and new kinds of exploration and analysis.

BobsChart

 

And of course, off to the right, are the business outcomes enabled by these different use cases for analytics.

I won’t repeat details of DB2 BLU Acceleration, IBM’s Big Data Platform or the PureData System for Hadoop as I blogged about them all before (see links for details). With that Beth Smith came on stage to other new announcements (the ones  not covered earlier by the Almaden event).

The focus she says is on fast (performance, deployment, time to value), easy (consumable, visual, guided) and smart (optimized, automated, domain-specific). The new announcements then:

  • SPSS Analytic Catalyst – a “statistician in the software”
    This is designed to provide an easy to use UI that allows non-statisticians to discover statistically interesting results in big data. The focus here is on helping to close the skills gap and make predictive analytics more accessible. It provides an automated environment combined with natural language explanations of the statistically interesting elements identified. The automation is extended with a drag-and-drop environment for drilling down, seeing if things have a relationship etc. Hundreds of columns can be supported and variables can easily be changed from targets to drivers etc.
  • SPSS Modeler support for text analytics
    SPSS Modeler has been extended to support text analytics so that these can be combined with structured analytics. The Big Data platform can be accessed from inside the Modeler environment as well as the SPSS Analytic Server
  • Cognos BI updates
    Cognos BI Mobile has a new UI, new interactive visualizations, extensible for future visualizations (on analyticszone.com). IBM has also linked Cognos to the Big Data infrastructure (supporting multiple Hadoop distributions) as well as both DB2 BLU and SAP HANA.  In addition the team has improved performance in things like active reports and mobile. Simplified user roles and licensing, improved and extended deployment patterns too.
  • Social Media Analytics
    SaaS based version of social media analytics added to the on-premise version.
  • Cognos Disclosure Management
    This wraps numbers with narrative and disclosures, pushes it through an edit and approval cycle so it can be published (as XBRL for instance).
  • Accelerated External Reporting Blueprint
    IBM partnered with Deloitte to use Cognos TM1 and Cognos Disclosure Management to handle statutory reporting and tax filing.

A real mix of announcements, some very tactical and practical ones and other more visionary and boundary pushing.

Beth went on to discuss some of the things they are working on in the labs. Collaboration, mobile and support for both cloud and on premise are common themes. One project is focused on using collaboration, workflow and mobile  in the performance management / dashboard environment. Tasks are presented, as they would be in a process management tool, and linked to tools like Cognos TM1. Tasks can have recommendations and macros built into them to help new users get through the workflow, for external reporting for example, more effectively.

Beth wrapped up by pointing out how important it is to build in expertise to these solutions, a point re-emphasized by Les. This leads to a discussion of AnalyticsZone.com where visualizations, a social media hub and downloads for personal tools have been available for a while.

Bob then introduced a new rapid approach to Big Data – “Stampede” – to get tutorials, training, IBM software and IBM expertise going quickly. 10 week engagement with “very aggressive” pricing as part of IBM Labs Services. IBM is also working with academic providers with more than 1,000 academic relationships for everything from guest lecturers to curriculum design to funding research.

At the end of the day, IBM is focused on delivering competitive advantage by combining Big Data with analytics of different types. Innovation and business-ready capabilities, a strong software infrastructure and ongoing, large scale investments in analytics.

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