Five Predictions for Advanced Analytics in 2010

With 2010 now upon us, I wanted to take the opportunity to talk about five advanced analytics technology trends that will take flight this year.  Some of these are up in the clouds, some down to earth.

  • Text Analytics:  Analyzing unstructured text will continue to be a hot area for companies. Vendors in this space have weathered the economic crisis well and the technology is positioned to do even better once a recovery begins.  Social media analysis really took off in 2009 and a number of text analytics vendors, such as Attensity and Clarabridge, have already partnered with online providers to offer this service. Those that haven’t will do so this year.  Additionally, numerous “listening post” services, dealing with brand image and voice of the customer have also sprung up. However, while voice of the customer has been a hot area and will continue to be, I think other application areas such as competitive intelligence will also gain momentum.  There is a lot of data out on the Internet that can be used to gain insight about markets, trends, and competitors.
  • Predictive Analytics Model Building:  In 2009, there was a lot of buzz about predictive analytics.  For example, IBM bought SPSS and other vendors, such as SAS and Megaputer, also beefed up offerings.  A newish development that will continue to gain steam is predictive analytics in the cloud.  For example, vendors Aha! software and Clario are providing predictive capabilities to users in a cloud-based model.  While different in approach they both speak to the trend that predictive analytics will be hot in 2010.
  • Operationalizing Predictive Analytics:  While not every company can or may want to build a predictive model, there are certainly a lot of uses for operationalizing predictive models as part of a business process.  Forward looking companies are already using this as part of the call center process, in fraud analysis, and churn analysis, to name a few use cases.  The momentum will continue to build making advanced analytics more pervasive.
  • Advanced Analytics in the Cloud:  speaking of putting predictive models in the cloud, business analytics in general will continue to move to the cloud for mid market companies and others that deem it valuable.  Companies such as QlikTech introduced a cloud-based service in 2009.  There are also a number of pure play SaaS vendors out there, like GoodData and others that provide cloud-based services in this space.  Expect to hear more about this in 2010.
  • Analyzing complex data streams.  A number of forward-looking companies with large amounts of real-time data (such as RFID or financial data) are already investing in analyzing these data streams.   Some are using the on-demand capacity of cloud based model to do this.  Expect this trend to continue in 2010.
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5 Responses

  1. How are mid-market companies using analytics today, and how will the greater availability of cloud-based BIaaS plays (so to speak) change their usage?

    • That’s a good big question with no short answer.

      – IBM recently published an interesting study (Voice of the CIO) that included about 160 mid market companies and their priorities for BI that is worth looking at.
      – There are numerous on-premises solutions for various aspects of BI that mid market companies are making use of.
      – BIaaS vendors are popping out of the woodwork and obviously one play is with the mid market firms.
      – It is possible that mid market firms will want more specific rather than generic BI tools – like sales planning, spend analysis, but it will be important for these to work together in a cloud environment.

      Contact me directly if you need more information.

  2. Fern
    great list – the only thing I would add is that I think there will be an increasing move to making tools for building advanced analytic models more accessible to non-quants
    JT

  3. Hi Fern, great article. Any views on how this sector will reflect in the Indian market?

  4. What’s the point of having data, if it is not knowledgeable and efficient. Data integration is vital as it represents value to the business, to the consumers and to the partners. Everyone wants quality data to be able to make better business decisions.

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