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SmartData Collective > IT > Cloud Computing > Trends in Smarter Business Analytics
AnalyticsBusiness IntelligenceCloud ComputingDecision Management

Trends in Smarter Business Analytics

JamesTaylor
Last updated: 2011/09/19 at 5:38 PM
JamesTaylor
3 Min Read
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Don Campbell, CTO Of IBM’s Business Intelligence group, presented on trends in smarter business analytics. He sees four focus areas – improving customer understanding, optimizing real-time decisions, better enterprise visibility and improved collaboration. All underpinned by managed, trusted data. IBM’s customers tell them that the 3 big challenges are

Don Campbell, CTO Of IBM’s Business Intelligence group, presented on trends in smarter business analytics. He sees four focus areas – improving customer understanding, optimizing real-time decisions, better enterprise visibility and improved collaboration. All underpinned by managed, trusted data. IBM’s customers tell them that the 3 big challenges are

  • A lack of understanding of how to use analytics
  • A lack of management bandwidth
  • A lack of skills

In addition companies are changing how they see analytics, focusing on more advanced and forward-looking analytics and less on management reporting.

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Don meanwhile sees several areas where future developments are important:

  • Mobility – more mobile devices, tablets, HTML 5 etc
    More and more about business users pushing IT not IT pushing to users. Increasingly about taking advantage of the devices GPS, and accelerometer for instance as well as pushing simple device-centric interfaces not simply replicating the traditional view on those devices.
  • Cloud and massive scale analytics
    Lots of interest in cloud implementations for massive scale etc. Interestingly this is an area where I am doing some research – check out smartdatacollective/predictive-analytics-cloud to register or take our upcoming survey.
  • Watson
    There is lots of interest in IBM’s Watson – both interest in its ability to interpret questions and use large amounts of data to answer questions as well as its ability to use multiple strategies to learn what works and what does not.
  • Geospatial and temporal analytics
    As mobile devices proliferate the need for geospatial and temporal aspects to analysis and predictions. Who is the most useful customer for me to visit when I have a few hours spare in my current location?
  • Consumable analytics
    Many organizations have very low adoption rates of analytics – stuck around 20% – so we must make it easier to consume analytics through automation (by building Decision Management Systems) as well as through better visualization.
  • Social media and social analytics
    This allows us to interact with customers in new ways and so has the potential to really change how we work.
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Copyright © 2011 http://jtonedm.com James Taylor

TAGGED: ibm
JamesTaylor September 19, 2011
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