By: Greta Roberts, CEO, Talent Analytics, Corp.
When beginning a new predictive analytics project, the client often mentions the importance of a “quick win”. It makes sense to think about delivering fast results, in a limited area, that excites important stakeholders and gains support and funding for more predictive projects. A great goal. It’s the implementation of the quick win in a
In anticipation of his upcoming Predictive Analytics World for Workforce conference co-presentation, Open Sourced Workforce Analytics: An Overview of 3 Algorithms for Common Predictive Modeling Situations, we interviewed Jason Noriega, Diversity Analytics Team Lead at Chevron. View the Q-and-A below to...
In anticipation of his upcoming conference co- presentation, Advanced Analytics and the Corporate Audit Function at Predictive Analytics World San Francisco, April 3-7, 2016, we asked Matthew Pietrzykowski, Senior Data Scientist at General Electric, a few questions about...
By: Richard Boire, Founding Partner, Boire Filler Group
Much work in predictive analytics and data science has been primarily focused around the business to consumer sector (B2C). Certainly predictive analytics solutions have been applied to the B2B sector but it pales in comparison to what...
In anticipation of his upcoming Predictive Analytics World for Workforce conference presentation, Big Data Driven Labor Scheduling, we interviewed Greg Tanaka, CEO at Percolata. View the Q-and-A below to see how Greg Tanaka has incorporated predictive analytics into the workforce...
In anticipation of his upcoming Predictive Analytics World for Workforce conference presentation, Finding Top Data Scientists for Your Organization: Optimize the Hiring Process with Analytics, we interviewed Michael Li, CEO at The Data Incubator. View the Q-and-A below to see...
By: Patrick Surry, Chief Data Scientist, Hopper &
Nicholas Radcliffe, Founder, Stochastic Solutions
If, as Niels Bohr maintained, an expert is a person who has made all the mistakes that can be made in a narrow field, we consider ourselves expert data scientists. After twenty years of doing what’s been...
By: Dean Abbott, Co-Founder & Chief Data Scientist, SmarterHQ
President, Abbott Analytics
When we build predictive models, we often want to understand why the model behaves the way it does, or in other words, which variables are the most influential in the predictions. But how can we tell which...
By: Neil Mendelson, VP, Big Data and Advanced Analytics, Oracle
Jeff Pollock, VP, Big Data Integration and Governance, Oracle
Companies big and small are finding new ways to capture and use more data. The push to make big data more mainstream will get stronger in 2016. Here are Oracle’s top 10 predictions: 1. Data civilians operate more...
By: Philip O'Brien, MIS and Portfolio Manager, Paychex
So you have gathered your data and completed your exploration and cleansing. You labored countless hours transforming the data and created a strong model that can revolutionize the way your company sees its clients, makes decisions and...
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