Monthly Archives: October 2013

The Myth of the Easy Button

eDiscovery Cat

With Judges  accepting application of Predictive Analytics, why haven’t we seen a massive conversion to technology based solutions?

Since the introduction of analytics to the eDiscovery space, there has been an assumption that once there was judicial acceptance there would be a massive migration to the faster, cheaper solutions leveraging the new technologies.  Studies  including the infamous TREC one have consistently shown that human review is far from flawless and consistent.  And yet, there has not been a mass exodus from linear human review to automated or semi automated solutions.  Why is this the case?

What  the Heck is TAR?

The resistance to fully embracing analytic solutions comes from several places, but one of the largest sources is an overall lack of understanding as to what predictive analytics can and cannot do.  And a false belief that to use Technology Assisted Review solutions (TAR) requires abdication of all control over…

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SAP Advances Analytics/BI Continuum, Broadens Use

Tableau Continues its Visual Analytics Revolution

Analyst Perspective - Tony Cosentino

In his keynote speech at the sixth annual Tableau Customer Conference, company co-founder and CEO Christian Chabot borrowed from Steve Jobs’ famous quote that the computer “is the equivalent of a bicycle for our minds,” to suggest that his company software is such a new bicycle. He went on to build an argument about the nature of invention and Tableau’s place in it. The people who make great discoveries, Chabot said, start with both intuition and logic. This approach allows them to look at ideas and information from different perspectives and to see things that others don’t see. In a similar vein, he went on, Tableau allows us to look at things differently, understand patterns and generate new ideas that might not arise using traditional tools. Cabot key point was profound: New technologies such as Tableau with its visual analytics software that use new and big data sources of information are…

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Predictive Analytics on Cloud: Major Drivers

Global IT Consulting


Predictive analytics can easily mine and turn a large volume of data into valuable business insights. This requires organizations to build statistical predictive modeling systems that demands significant time and resources with niche skill sets. It’s just a matter of time that organizations start realizing and moving their predictive and statistical analytic systems onto the cloud.

Drivers for cloud are not just dealing with big data, niche skills, and time it takes to build the system, but also the volume of consumer’s behavioral information that is available online, which can help in building a full proof predictive modeling system.

When you plan to build and deploy a predictive model, one of the major bottle necks would be to convert your data into a format that facilitates building and deploying predictive models, The transformation of data however is often a series of database operations (group by, join, where clauses), Numerical…

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Predictive Analytics with Endeca


The opportunities and challenges to delivering real world Predictive Analytics are exciting.  They’re not trivial efforts, and they require a level of collaboration between Business and IT that can be rare.  However when the stars align the forecasts they produce can be game changers.  And a BI solution that doesn’t change the game for its business is arguably a waste of time.

Oracle Endeca Information Discovery is not really a Predictive Analytics tool.  The Text Mining through Lexalytics provides one powerful data mining model, but that’s the only one.  Plus it’s part of the data ingest and upstream from Studio.  We’ve interfaced with R from Integrator enough to know during the ETL stage just about any external data mining model is effectively available.  Some level of classification and association might be suggested through Studio’s data exploration, but I’d argue this produces business questions and is a far cry from the…

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Mobile Analytics Form a Two-Way Street Between the Past and the Future

IT Connection

Summary Bullets:

  • There are great advantages to disseminating analytics smarts to mobile users such as sales persons.
  • Real innovation, however, comes when you combine that dissemination with the collection of data points.

I spent a few hours yesterday listening to a number of SAP ISV partners including ExpertIG, Rapid Consulting and Liquid Analytics demonstrate mobile software built to support the wholesale market.  I know, that doesn’t sound incredibly exciting.  Yet, long before the expiration of my admittedly short attention span, I was struck squarely by what was for me a stunning realization.  Big data should be as much about collecting data as it is about gleaning knowledge from that data.

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