Predictive Business Analytics
December 3-5, 2019
Learn analytical tools and techniques for anticipating and exploiting the changing competitive environment by mining data to determine the influences on business, society, politics, the economy, the environment, and technology. Identify immediate actions you should take to exploit opportunities and avoid catastrophes. Your action plan will propel your business forward and drive the application of data science in your industry.
Data science, machine learning and big data promise huge operational payoffs by focusing limited resources, tailoring customer relations and fixing problems before they appear. Explore applications to your business. Get hands-on experience (no coding required) applying data science to business issues. This course employs a series of representative business use cases and provides first-hand experience with key techniques of data science.
- Understand what data science can and cannot do for your business
- Translate business goals into powerful data science projects
- Track business performance in the context of the current dynamic business environment
- Gain hands-on experience with the essential data science techniques
- Draw hidden insights from the data you already have using supervised and unsupervised machine learning
The participant should have a basic familiarity with Microsoft Excel for the exercises.
Recommended for managers, business leaders, business analysts, consultants, technical personnel, scientists, engineers, and non-programming individuals who support business operations who need to know about and can benefit from a greater understanding of what business analytics is and can do for your business.
Overview of Analytics (Big Data and Data Mining)
Data versus Intuition
The Business Context of Data Mining and Analysis (Business Metrics)
Confirmation Bias and Other Barriers to Effective Analytics
Sources of Data for Analytics
Benefits and Misuses of Business Analytics
What data science can do for your business
How to draw credible insights from data
Use case 1: Which mortgages are most likely to be refinanced? Classification
Use case 2: Which customers are likely to have a baby soon? Multiple regression
Use case 3: Segmenting customers into interest groups. Clustering
More advanced techniques of data science
Day 3 (half day on data science and half day on preparing a personal plan)
Use case 4: Text mining (Which tweets relate to my company?)
Neural Networks and Deep Learning
Apply Business Analytics to Your Job
Develop a Personal Plan to Use Analytics to Enhance Your Business and Career
The text, Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die, 1st Edition, Eric Siegal (Wiley Press, 2013), and lecture notes are distributed on the first day of the course.
Chris Christensen, MS, MBA, President, Christensen Associates, Inc., a management consulting firm, Playa del Rey, California. For three decades, Chris Christensen was a program and project manager in the aerospace, high technology components manufacturing, and systems integration industries. In addition, Mr. Christensen has worked both as an intelligence analyst and a consultant to government agencies collecting and analyzing data to predict future events.
In 1992, Mr. Christensen launched Christensen Associates, Inc., to train executives, managers, and senior staff in effective business management. He coaches executive teams, facilitates off-site retreats, and leads on-site workshops in forecasting future business and technological breakthroughs, strategic planning, new product development, and competitive intelligence.
Mr. Christensen is a certified Program Management Professional, Six Sigma Black Belt, and Certified Quality Manager. He teaches courses in strategic planning, competitive intelligence, and futures research at UCLA and Loyola Marymount University. He is the co-author of the ASQ Handbook for the Certified Quality Process Analyst and is the author of Solving Organizational Problems.
Carol Jacoby, PhD, specializes in analytical techniques for data science, system effectiveness prediction, systems engineering and decision analysis. She has 28 years of experience in systems engineering at Hughes Electronics and Rockwell International. She led Hughes’ Mission Analysis Center of Excellence in developing, simulating, and analyzing complex systems of systems for defense, transportation, and other areas. She was one of the first people to apply systems engineering and analytical techniques to highway transportation, including early work on driverless vehicles. She has taught these techniques since 2001 to government agencies and major corporations.
She is the author of the book Simple Spreadsheets for Hard Decisions, which brings many of these decision techniques to a general audience. She also co-authored the Systems Engineering Guidebook for the Federal Highway Administration. Dr. Jacoby has been honored through the District One Toastmasters’ elite Speakers Bureau, multiple Hughes and Raytheon Achievement Awards, the Hughes Doctoral Fellowship, and Phi Beta Kappa.
Dr. Jacoby is an internationally recognized research mathematician, with several recent publications in peer-reviewed journals and a new book written for advanced graduate students and researchers. She earned her PhD at the University of California, Irvine, her MS at Northeastern University, and her BA at UCLA, all in mathematics.
For more information contact the Short Course Program Office:
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