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Posts Tagged: Product News
Decision Modeling and DMN for IBM Customers – New Brief

Decision Modeling and DMN for IBM Customers – New Brief

We have a new Leading Practices brief available - Decision Modeling and DMN for IBM Customers. IBM has long been a leading player in business rules management systems and Decision Management Solutions has many customers using IBM Operational Decision Manager in North...

Decision Modeling and IBM Operational Decision Manager

IBM yesterday announced that Operational Decision Manager v8.10 (ODM - IBM's Business Rules Management System) will be available in December and will support decision modeling. This is great news as it will bring the Decision Composer functionality IBM has been...

Enterprise Scale Analytics with R – New White Paper

As R has become more popular, the role of analytics has become increasingly important to organizations of every size. Increasingly, the focus is on enterprise scale analytics—using advanced, predictive analytics to improve every decision across the organization....

IBM #WatsonAnalytics Live Blogging Series

James live blogged from this week's IBM Watson Analytics event in New York earlier this week. Don't miss the series posted to www.jtonedm.com. Table of contents for IBM Watson Analytics Cloud IBM Watson Analytics Cloud Announcement KickOff IBM Watson Analytics Cloud...

New Decision Management MarketScape from IDC

Brian McDonough has been writing (with Dan Vesset, Steve Hendrick, Henry Morris and others) on Decision Management at IDC for many years and he has recently published an IDC MarketScape: Worldwide Decision Management Software Platform 2014 Vendor Assessment. The...

Challenges Scaling Open Source R – Part 2

I recently did some research on the requirements for enterprise-scale analytics and the challenges of using open source R in this context. In my first post (Requirements for Enterprise Scale Analytics with R – Part 1) I outline some of the requirements I see for...

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...

Great Hurwitz Report on Predictive Analytic tools

The Hurwitz Group just published their Victory Index for Predictive Analytics. This is a great report on the core predictive analytic vendors written by Marcia Kaufman and Daniel Kirsch. The report covers Angoss, IBM, Megaputer, Pegasystems, Predixion, RapidMiner, Revolution Analytics, SAS, SAP, StatSoft. The report aims to assess four things about each vendor:

  • Vision – how good the company’s strategy for predictive analytics is
  • Viability – how sustainable the company’s presence in the market is
  • Validity – how customers perceive the technical benefits and capabilities of the company’s product
  • Value  – how much business value customers achieve with the company’s product

This assessment is based on vendor surveys, vendor s

Pegaworld 2014 – Pega 7 Summary

Kerim Akgonul came up next to talk products, in particular Pega 7. Pega 7 was released last year and is being used around the world. Pega 7 focused on several elements:

  • Visibility through the common case interface
  • Speed and accuracy through automation of processes and decisions
  • Speed and accuracy also of development, making it easier and quicker to develop applications and adapt them over time.
  • Anticipating customer needs through new data integration capabilities that support streaming data and “Big Data” delivering predictive and adaptive analytics built using this data.
  • User adoption by redoing the UI engine so that it is easy to deliver engaging,usable interfaces.

Pega 7 also supported cloud deployment, social/mobile and all the usual enterprise capabilities.

 

Pega 7 is also the platform for their CRM applications – Next Best Action Marketing, Customer Process Management and Sale

Decision Management Market Highlights Q1 2014

We published our Decision Management Market Highlights Q1 2014 today. Here is an excerpt: There have been interesting developments in the Decision Management market this quarter. In particular the focus is clearly shifting from Decision Management simply as a better...

Standards in Predictive Analytics: Futures

In this series so far we have discussed a number of standards – R, PMML and Hadoop – that are well established. There are also some future developments that are worth considering—the emergence of the Decision Model and Notation standard, growing acceptance of Hadoop 2 and planned updates to PMML specifically.

As regular readers of this blog know, the Object Management Group recently accepted the Decision Model and Notation standard as a beta specification for finalization in 2014. DMN provides a common modeling notation, understandable by both business and technical users, that allows decision-making approaches to be precisely defined. These decision models can include the specification of detailed decision logic and can model the role of predictive analytics at a requirements level and at an implementation level through the inclusion of PMML models as functions.

Standards in Predictive Analytics: PMML

Continuing my series on standards in Predictive Analytics I am going to talk first about PMML. PMML is an XML standard for the interchange of predictive analytic models developed by the Data Mining Group. The basic structure is an XML format document that contains a header, a data dictionary, data transformations and one or more models each consisting of a mining schema based on the type of model, a target and other outputs such as measures of accuracy. PMML started in 1998 and the most recent release was 4.1 in 2011. The 4.x releases marked a major milestone with support for pre- and post-processing, time series, explanations and ensembles. Support for PMML is widespread and growing with an active community and many analytic vendors are either members of DMG or provide support for the standard in their products.

PMML has particular value for organizations as they move away from a batch scoring mindset to a more real-time scoring approach.

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