big data

The Value of Predictive Analytics and How Using Decision Modeling Helps You Succeed

May 27, 2015 10:00 am PDT, 1:00 pm EDT Register here. Successful predictive analytic projects follow a well-defined approach from requirements to modeling, implementation and deployment, embedding the analytic results in operational systems that improve business performance. In this live webinar, James Taylor, CEO and Principal Consultant at Decision Management Solutions and Matt Kitching, Senior […]

Decisions, Decision Management and an architecture for digital transformation

Ray Wang of Constellation Research published a report early this year “The Elements of Business Architecture for Digital Transformation.” In the report Ray identifies some interesting boardroom priorities (this is just some of them): Consistent Customer Experience Mass automation Insights-driven business models Cost-effective regulatory compliance All of these are reasons given by our clients as […]

Using Decision Modeling to make Predictive Analytics more pervasive

  Back in May of last year, Wayne Eckerson published “Making Predictive Analytics Pervasive“. It’s a great report with some really useful data but one of the key headline result is that implementation rates are not rising – in fact fewer organizations are reporting successful implementation of predictive analytics (from 21% to 18%). This despite […]

Analytics Capability Landscape Research Report and Infographic

We have just published the Analytics Capability Landscape Research Report and Infographic. This new research report looks at the increasingly broad portfolio of analytic capabilities available to enterprises today asking the real question – what situations need which capabilities, who is the target user for these capabilities, and how can this portfolio of capabilities be […]

Live from IBM Insight 2014

For live updates from IBM Insight 2014, follow @jamet123 and www.jtonedm.com. Here are the live blogging updates from conference: Table of contents for IBM Insight 2014 Opening #IBMInsight Keynote: Seize This Moment: Envision Your Future #IBMInsight Keynote: Envision you journey: Are you ready for real-time decision-making? #IBMInsight Powerful Analytics for Everyone #IBMInsight Keynote: Seize this […]

Upcoming Webinar: Analytics Maturity Curve or Landscape? Your Questions Answered

November 6, 2014 2 pm ET/11 am PT Register here. What’s the difference between the various analytic capabilities? How do I map available analytic capabilities to my business needs? What’s the right combination of capabilities for me now and in the future? What should I look for in each of these capabilities to make sure […]

Requirements for Enterprise Scale Analytics with R – Part 1

I recently did some research on the requirements for enterprise-scale analytics and the challenges of using open source R in this context. In this first post I wanted to outline some of the requirements I see for enterprise scale analytics and in a second post I will discuss the challenges of R in that context. As advanced […]

Some thoughts on KDNuggets’ top trends ahead of Strata Hadoop NYC

Gregory over at KDNuggets had an interesting post with some Top Analytics and Big Data trends ahead of Strata Hadoop NYC Conference based on input from their readers. Three trends struck me: The challenge of communicating complex analyses to non-technical clients/partners We are having increasing success using logical decision models to show how data and analytics drive better […]

Decision Management and a business perspective on Big Data

Check out this article – Business leaders need Rs not Vs: The 5 Rs of Big Data. I met Merritt,the author, at the TDWI Solution Summit on Advanced Analytics this spring. In the post, and in his subsequent work, he makes some great points. I really like his 5Rs and think they illustrate the power of […]

The Economist: Big Data, Little Decisions

There was a fascinating piece in the Economist last week – Little things that mean a lot. This piece really resonated with me – even the title sounds a lot like my mantra of “Big Data, Little Decisions” (you can see a selection of the articles and webinars I have given on this topic here). So what were the critical points Schumpeter made?

First the point that constant experimentation and rapid iteration is critical when trying to get value from all this data. Experimentation is often the skill we tell clients they most need to develop and we regularly stress the importance of putting in place the infrastructure and processes for ongoing decision results analysis. To maximize the value of big data and beco