From Predictive to Prescriptive Analytics and Beyond
Date: Feb 15, 2017 (Wednesday) 7:00 - 9:00 pm (Registration starts at 6:30pm)
Venue: ITRI Int’l, 2870 Zanker Rd., Suite #140, San Jose, CA
No one has the ability to capture and analyze data from the future. However, there is a way to predict the future using data from the past. It’s called predictive analytics, and organizations do it every day.
Predictive analytics is the practice of extracting information from existing data sets in order to determine patterns and predict future outcomes and trends.
Applied to business, predictive models are used to analyze current data and historical facts in order to better understand customers, products and partners and to identify potential risks and opportunities for a company. It uses a number of techniques, including data mining, statistical modeling and machine learning to help analysts make future business forecasts.
Though predictive analytics has been around for decades, it is a technology whose time has come. More and more organizations are turning to predictive analytics to increase their bottom line and competitive advantage. Why now?
- Growing volumes and types of data, and more interest in using data to produce valuable insights
- Faster, cheaper computers
- Easier-to-use software
- Tougher economic conditions and a need for competitive differentiation
In this seminar, Dr. Kao will present these current topics of interest, data mining, and the evolution of business analytics from descriptive, to predictive, to prescriptive methods, and their many applications. Future cognitive analytics trends will also be briefly covered.
Dr. William Kao received his BSEE, MSEE and PhD from the University of Illinois Urbana-Champaign. He worked in the Semiconductor and Electronic Design Automation industries for more than 30 years holding several senior and executive engineering management positions at Texas Instruments, Xerox Corporation, Cadence Design Systems.
Dr. Kao has authored more than 40 technical papers at IEEE Journals and Conferences, and holds eight software and IC design patents. He was an Adjunct Professor at UCLA Electrical Engineering Department where he taught courses in computer aided IC design.
Dr. Kao is a Senior Member of IEEE, and was one of the founding members of IEEE-Circuits and Systems - Silicon Valley Chapter, where he was Chapter Chair in 2005 and 2006.
Dr. Kao currently teaches Renewable Energy, Clean Technology and Business Sustainability courses at the University of California Santa Cruz, Silicon Valley Extension. Dr. Kao current interests include the subjects of Energy, Environment and Education. He teaches and is a frequent lecturer on various Emerging Technologies. In the past five years he
has given over 50 talks and seminars on Clean Technology, Renewable Energy, Business Sustainability, Big Data, IoT, Smart Cities, Sensor Networks, Innovation, AR/VR, Robotics, AI and 3D Printing.