David has spent over 30 years developing and perfecting data driven strategies to help clients with their analytical needs. David specializes in price optimization, demand/supply forecasting, valuation analytics, market research, and strategic planning. David used his comprehensive knowledge of data and analytics to develop the DECIPHER™ Business Intelligence Platform, which Competitive Analytics uses to deliver all nine functions of the business intelligence process. For David, analytics is not just a profession . . . it’s his passion.
On weekends, David even enjoys researching and analyzing baseball or basketball statistics to discover what is truly driving his favorite teams’ performance. David has a Bachelor of Finance and M.B.A. from Arizona State University, completed his first year of a PhD in Psychology, and is a member of the National Association of Economists and National Speaking Association. David is a native New Yorker, but lives in Villa Park, California with his wife, Erika. They have two children, their son August and daughter London. If David is not sifting data or spending time with his family, he can be found at home in his state-of-the-art recording studio writing and recording music.
Michael Ponton has 10 years experience in economic analysis, statistical analysis, financial analysis, analytical modeling, market intelligence, idea generation and implementation, strategic planning, consumer behavior analysis, and executive management. Michael’s unique core competencies include solving complex problems, creating innovative economic forecasting models, developing proprietary valuation/forecasting models, programming customizable Excel models via Visual Basic, and synthesizing complex concepts into working models. Michael started working at Competitive Analytics on October 11, 2005.
Prior to his active role as Director of Analytics at Competitive Analytics, he attended California State University Fullerton for his undergraduate degree in Business Administration with an emphasis in Economics and his graduate degree in Economics with an emphasis in Finance. Michael graduated top of his class in his masters program and received numerous awards for being the only student to achieve a 4.00 in the core economic program.
Mastering Predictive Analytics
Every decision by definition is a prediction about the future. And because we’re now in the early stages of the “epoch of big data”, one of the most vital functions for all organizations is “predictive analytics.” In fact, predictive analytics ranked #1 on a list of all analytics applications in which 84% of all companies now use or plan to use within the next 3 years. Moreover, predictive analytics is now (or rapidly becoming) a vital part of the decision making process in business, science, politics, sociology, psychology, sports, entertainment, music, government, non-profits, and any field and industry you can think of.
This course will leverage two of the most powerful analytics tools available: Alteryx and Tableau. Students will learn how to build predictive models using both Alteryx and Tableau while learning the 20 Core Principles of Forecasting Expertise each step of the way. Students will also learn valuable case studies of how predictive analytics has been successfully applied in the “real world” – gaining powerful insights and techniques from innovative and custom forecast models built for Honda, Toyota, Irvine Company, and others. This course is specifically designed for students who want a practical, powerful, and hands-on recipe for mastering predictive analytics.
This course will also focus on how students can develop more accurate forecasts for better decision making via the 20 Core Principles of Forecasting Expertise:
• Understanding different philosophies of forecasting
• Identifying and learning from master forecasters
• Formulating the forecast question via an organization’s strategic and tactical objectives
• Planning your forecast while understanding your audience
• Finding reliable external data sources
• Connecting to internal data sources and leveraging dark data
• Preparing and cleaning time series data
• Blending different data sources
• Selecting forecast methods
• Building modeling tables
• Conducting quick forecasts
• Utilizing statistical, mathematical, econometric, and analytical tools
• Building analytic work flows
• Developing comprehensive what-if scenario-based forecasts
• Evaluating and contextualizing forecast output
• Designing dashboards and the art of data visualization
• Presenting and reporting forecasts
• Using forecasts and the decision making process
• Monitoring and benchmarking forecasts
• Revising and evolving forecasts
- Superforecasting: The Art and Science of Prediction by Philip E. Tetlock and Dan Gardner https://www.amazon.com/Superforecasting-Prediction-Philip-E-Tetlock/dp/0804136718
- The Signal and the Noise: Why So Many Predictions Fail – but Some Don’t by Nate Silver https://www.amazon.com/Signal-Noise-Many-Predictions-Fail-but/dp/0143125087/ref=pd_sbs_14_img_1?_encoding=UTF8&psc=1&refRID=PBS5JN3DGX2JPQRQ632N
- Principles of Forecasting: A Handbook for Researchers and Practitioners by J. Scott Armstrong https://www.amazon.com/gp/product/0792379306/ref=oh_aui_search_detailpage?ie=UTF8&psc=1
- A Practitioner’s Guide To Alteryx by USEReady https://www.amazon.com/Practitioners-Guide-Alteryx-USEReady/dp/0692447954/ref=sr_1_1?ie=UTF8&qid=1489017064&sr=8-1&keywords=alteryx
- Learning Tableau 10 by Joshua N. Milligan https://www.amazon.com/Learning-Tableau-10-Joshua-Milligan/dp/178646635X/ref=sr_1_1?ie=UTF8&qid=1489017111&sr=8-1&keywords=tableau