Data Mining

Decision Modeling and CRISP-DM for Modern Data Science Projects

Many data science projects use the popular and well established CRISP-DM methodology. However, CRISP-DM has limitations especially regarding business understanding and deployment. The decision modeling process and the graphical decision requirements diagram addresses these challenges. CRISP-DM Popular, but with Limitations Gregory Piatetsky of KDnuggets writes following the KDnuggets Data Mining Methodology Poll: “CRISP-DM remains the […]

Great New Case Study – Bringing Clarity to Data Science and Analytic Projects

We have been helping several organizations improve their analytic and data science projects. Like many users of analytics, these organizations find that their analytic teams often lack a clear understanding of the business problem, resulting in projects that lose their way or produce analytic  models that don’t get operationalized, deployed or used. We have helped […]

Predictive Analytics World 2017: The Role of Decision Modeling in Creating Data Science Excellence

Join me and Tina Owenmark of Cisco when we speak on The Role of Decision Modeling in Creating Data Science Excellence at Predictive Analytics World in San Francisco. Cisco’s Data Science Office focuses not just on data science, but also on shaping the questions and answers for Cisco’s operational groups. They focus not on technology or […]

Decision Modeling Brings Clarity to Analytics – New Podcast

The biggest challenge facing organizations adopting analytics is closing the gap between business value and analytics results. This is becoming increasingly serious as more organizations make investments in data mining, predictive analytics, data science, machine learning and all forms of analytics. Ensuring that these investments in analytics and analytic technology show a return means understanding how […]

Can Machine Learning Solve Your Business Problem?

One of my LinkedIn contacts recently pointed to this great little article on HBR – How to Tell If Machine Learning Can Solve Your Business Problem – and it makes some points that show the potential for decision modeling to help you better apply machine learning and other analytic techniques. The author begins by pointing out that automation is […]

Some Analytic and Data Science Predictions 

“Making predictions is hard, especially about the future” is a well known witticism. When it comes to making predictions about how companies will make predictions, it can be even harder to know what to say. Nevertheless, the folks over at KDnuggets recently asked some of the leading experts in Data Science and Predictive Analytics for some thoughts on developments in 2016 and trends for 2017. I was one of those that participated and you can see the article here – Data Science, Predictive Analytics Main Developments in 2016 and Key Trends for 2017. Several key themes emerged from the various expert responses:

Analytics Teams: Before You Deploy

As I discussed in my earlier post, analytics or data science teams know that two key challenges for analytics projects are making sure you solve the real business problem (framing the problem) and making sure you can operationalize the result (deployment).  In this second post I am going to talk about deployment.

How to Succeed with Advanced Analytics at Scale

The webinar has taken place. You can view the recording here. Leading organizations today are looking to scale their advanced analytics capabilities, especially data mining and predictive analytics, to improve business performance, reduce fraud and improve customer responsiveness. However traditional analytic project approaches are hard to scale and difficult to implement in the real-time environment […]

Version 7 of The Decision Management Systems Platform Technologies Report

We’ve posted Version 7 of our popular Decision Management Systems Platform Technologies Report with new content on The Analytics Capability Landscape. We also welcome new vendors Blue Yonder and Erudine to the platform vendor index. Overview Organizations are adopting a new class of operational systems called Decision Management Systems to meet the demands of consumers, regulators and […]

The Value of Predictive Analytics and Decision Modeling – Webinar Presentation and Recording

The presentation and recording from our recent webinar, The Value of Predictive Analytics and Decision Modeling, are now available. 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 recording, James Taylor, CEO and Principal Consultant […]

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