analytic model

FICO has recently acquired InfoCentricity, makers of two advanced analytics products – Xeno (for building predictive scorecards, reviewed here) and StrategyTrees (decision trees). InfoCentricity has about 40 clients (some with over 100 modelers, some smaller). Most of these companies are also FICO clients though not generally for analytic modeling tools. Clients use the tools in [...]

I recently gave a presentation at bpmNEXT showing how you can apply decision modeling, using the new Decision Model and Notation standard, to build simpler, smarter and more agile processes. The actual presentation was recorded and I will blog when it goes live but as part of preparing I recorded the demo itself and we [...]

There was an interesting article from McKinsey this month – The benefits—and limits—of decision models – by Phil Rosenzweig. As Phil points out using models (and he is talking about analytic models) helps avoid common biases that undermine leaders’ judgments such as over confidence, a focus on recent data etc. And I would add not just leaders – it also [...]

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 [...]

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 [...]

With the fourth post in this series I am going to talk about Hadoop – something with even more hype than R or predictive analytics. As we all know the era of Big Data has arrived. As anyone who reads the IT or business press knows, there is more data available today,  this data is no longer [...]

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 [...]

I am working on a paper, for publication in early 2014, on the role of standards such as R, Hadoop and PMML in the mainstreaming of predictive analytics.  As I do so I will be publishing a few blog posts. I thought I would start with a quick introduction to the topic now and then [...]

I am giving the opening keynote for the BIWA Summit 2014 January 14-16, 2014 at the Oracle HQ Conference Center in Redwood Shores, CA. It’s an Oracle-focused event, obviously, with some novel and interesting use cases of Oracle Big Data, Exadata, Advanced Analytics/Data Mining, OBIEE, Spatial, Endeca and more. There are opportunities to get hands-on experience with products in [...]

Valen Analytics has been around since 2004 and is focused on providing proprietary data, analytics and predictive modeling to the Property and Casualty market with 25 customers in production. To help carriers manage and segment their portfolios to drive underwriting profitability, Valen develops productized models based on pooled consortium data for carriers. Valen’s InsureRight platform [...]

Karl Rexer just published his summary of this year’s Rexer Data Mining survey. As always there’s lots of good information but here are my favorite takeaways: As in our own work on Predictive Analytics in the Cloud, the survey fond that a focus on customers and on customer experience/engagement was top of mind. CRM/Marketing is [...]

i4C Analytics is focused on delivering advanced analytic applications for specific industries and business decisions. These packaged analytic applications apply predictive analytics in real-time in a highly automated environment. The applications use automated analytic model creation as well as allowing data scientists and predictive analytic professionals to integrate their own models to solve the business problems [...]

I recently gave a webinar on the results of our Predictive Analytics in the Cloud research (you can watch a replay here on Information Management). During the webinar we had some great questions and, as I did not get to all of them, I promised to write a blog post to address them. Meanwhile the [...]

The old way: Big data is a hot topic. Big Data was coined as a term by Gartner to mean data that has Volume (more data), Variety (of many types) and Velocity (that arrives more rapidly). Value is extracted from big data using advanced analytics such as data mining and predictive analytics. This data can [...]

Neil focused his session on Analytics. Analytics, he says, has roared to the front office in recent years (driven in part by the explosion of data and data management technology). Big, as in Big Data, is relative. The rate of increase has not particularly changed in recent years but the rate of increase is being [...]

This is the last week for our 2013 survey on Predictive Analytics in the Cloud – Use Cases, Trends and Big Data.  Please go right now and take the survey here – it’s quick , anonymous and you have a chance to win a $100 Amazon gift card. There’s been tremendous growth cloud and predictive analytics both [...]

It’s been a while since I got an update from Cloudera (last time was in 2010, here). Since then, obviously, much has changed. Back in 2010 Cloudera was focused on storage and batch processing against this data with little focus on advanced analytics. Today, Cloudera has added support for real-time SQL queries through improvements in [...]

Most software products have multiple opportunities for using predictive analytics to enhance decision-making. Because the use of predictive analytics is new for many software companies, and because handling decisions explicitly is also new, care must be taken not to bite off too much at once. A land and expand strategy that begins with a localized [...]

For a software company it is also important that this automation scales appropriately. In particular any automated analytic model development tool you use should provide flexibility in deployment to match your own, manage any variability between your customers’ data models and be easy to deploy, focused on the “last mile” of analytic model development. For most [...]