Posted By: James Taylor | Posted On: 6th November 2014 |
Here is a useful set of Decision Management Assets on Modernizing Operational Decisions from SAS Software with Decision Management Solutions’ CEO James Taylor. The set includes two decision management videos – one aimed at business users and one at IT professionals: For Business Users the first video is an interview between Fiona McNeil of SAS and Jame […]
Posted By: James Taylor | Posted On: 17th October 2014 |
FICO Analytic Modeler is FICO’s in-browser analytic tool suite – the evolution of the Model Builder product line post the InfoCentricity acquisition. These offerings are part of the FICO Analytic Cloud, a cloud-based environment for building and managing analytic models and deploying analytics into decisioning applications. It also features a marketplace for analytic solutions. The […]
Posted By: James Taylor | Posted On: 17th September 2014 |
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 report has an IDC MarketScape figure, IDC’s opinion on the Decision Management market, process and software as well as some […]
Posted By: James Taylor | Posted On: 22nd May 2014 |
Angoss recently released an end to end scorecard building tool –ScorecardBUILDER – based on the same underlying workflow capabilities released in Angoss KnowledgeSEEKER 9.0 (reviewed here). This product is designed to automate or otherwise streamline time consuming manual steps in the process of building a predictive scorecard.
As noted, ScorecardBUILDER is based on the new workflow-centric look and feel Angoss has recently released. This is extended in a number of ways for the ScorecardBUILDER tool:
There’s a helper for adding optimal binning and weight of evidence for a dataset. Each variable can then be assessed, visualized and optimized so that it is monotonic – trending in a single direction – and predictive. This helper creates the variables using a Weight of Evidence transformation.
A new logistic regression node is added for use in the workflow. This buil
Posted By: James Taylor | Posted On: 7th May 2014 |
SAS® Model Manager is getting an update soon to release 13.1 (I last blogged about Model Manager 3.1). The vision of SAS Model Manager going forward is to streamline the integration of predictive modeling into the overall environment, make it easier to operationalize analytical models, expand the model portfolio management capabilities and improve governance and monitoring of large numbers of models.
The new release will be standardized on the web-based application framework, making SAS Model Manager 100% browser-based – importing models, setting up champion-challenger, viewing performance etc. This web interface also makes these capabilities easier to access from within the SAS Decision Manager environment (reviewed here which includes the SAS Model Manager functionality).
Posted By: James Taylor | Posted On: 1st May 2014 |
SAS® Enterprise Miner recently got a major release – 13.1 – focused on machine learning, scalability and productivity. It’s been a while since I blogged about SAS Enterprise Miner (last review here) so this might not be a complete list of the improvements since then.
The machine learning focus added High Performance Support Vector Machines and Clustering while upgrading the HP Neural Network and Random Forest algorithms. From a scalability perspective the Principal Components, GLM, Bayeisan and Time Series Data Mining algorithms were all updated for high performance (multi-threaded parallelism etc). The high performance algorithms work the same and are dropped into SAS Enterprise Miner as nodes the same as always. These high performance data mining algorithms have been added in each of the last few versions. The intent of all this work is to support modelers so they can use all the data th
Posted By: James Taylor | Posted On: 10th February 2014 |
I first got a briefing on Dulles Research Carolina back in 2010 and I recently got an update. Dulles Research was founded in 2005 and came to market with Carolina, their SAS to Java convertor, in 2009. A U.S. patent was awarded to Dulles last year for the SAS to Java conversion process.
At its core, Carolina takes all aspects of Base SAS (Macros, Data Steps, PROCs, SAS data sets) and generates Java code from them. Dulles Research offer an execution engine that runs SAS programs in batch as a Java executable (Carolina), a Java generator that creates a JAR for processing a single record in Java (Carolina for Integration) and generators for Hadoop MapReduce jobs and database UDFs (Carolina for Hadoop and Carolina for In-Database). All the products rely on the same, patented, core Java genera
Posted By: James Taylor | Posted On: 26th December 2013 |
Back in 2008 I wrote this post – The small impact of business rules on the big players, bemoaning the lack of serious investment in business rules on the part of major software companies. As we enter 2014 I thought I would revisit this post and consider what a difference 5 years makes. Let’s consider some of the world’s top enterprise software vendors:
IBM has become a major booster for both Decision Management and business rules. The old ILOG product is now Operational Decision Management and has seen significant and continuous investment since IBM acquired it. Decision Management is one of three pillars of IBM’s Smarter Process initiative and every year it seems to have more visibility at events like IMPACT as well
Posted By: James Taylor | Posted On: 9th July 2013 |
I recently checked out The Evolution of Decision Making – How leading organizations are adopting a data-driven culture, a new white paper from the Harvard Business Review sponsored by SAS: People have long preached the benefits of relying on data and insights from business intelligence (BI) and analytics to help make better and timelier decisions. A reliance […]
Posted By: James Taylor | Posted On: 27th June 2013 |
Big Data is often described in terms of an increase in volume, an increase in velocity and an increase in variety: More data, of more types, arriving more quickly. In this short series of blog posts I will discuss the impact of each aspect of Big Data on Decision Management Systems – systems designed to […]