Putting Machine Learning to Work in Your Enterprise
TDWI Speaker: Fern Halper, TDWI VP and Senior Research Director
Date: Tuesday, September 12, 2017
Time: 8:00 a.m. PT, 11:00 a.m. ET
Everyone is talking about machine learning—software that can learn without being explicitly programmed, machine learning (and deep learning) can access, analyze, and find patterns in big data in a way that is beyond human capabilities. The technology is being used in a wide range of industries for use cases including fraud prevention, predicting crop yields, preventing and mitigating natural disasters, predictive maintenance of enterprise assets, and improving supply chain efficiencies.
The concept of machine learning is not new; in fact, some machine learning algorithms have been around for decades, and machine learning algorithms are often used in predictive analytics. What’s new is that organizations are using machine learning against large-scale data, and they are automating and operationalizing machine learning in business systems.
So, what does it take to make machine learning work in an enterprise? What features are needed and how do organizations get started? Join TDWI Research VP Fern Halper for a lively conversation with Mike Gualtieri from Forrester Research and experts from SAP to learn more about deploying enterprise-level machine learning.
You will learn:
- What are the market trends to watch in enterprise machine learning?
- What capabilities do you need for enterprise-scale machine learning?
- How is machine learning utilized in-database and in-place?
- What best practices are recommended for getting started?
VP, Principal Analyst Serving Application Development & Delivery Professionals
Mike's research focuses on software technology, platforms, and practices that enable technology professionals to deliver prescient digital experiences and breakthrough operational efficiency. His key technology and platform coverage areas are big data and IoT strategy; Hadoop/Spark; predictive, streaming, and prescriptive analytics; and machine learning, data science, AI, and emerging technologies that make software faster and smarter. Mike is also a leading expert on the intersection of business strategy, architecture, design, and creative collaboration. Mike is a recipient of the Forrester Courage Award for making bold calls that inspire leaders and guide great decisions.
Mike has more than 25 years' experience in the industry helping firms design and develop mission-critical applications in e-commerce, insurance, banking, travel/hospitality, manufacturing, healthcare, and scientific research for organizations including NASA, eBay, Bank of America, Liberty Mutual, Nielsen, EMC, and others. He has written thousands of lines of code, managed development teams, and consulted with dozens of technology firms on product, marketing, and R&D strategy.
He is a frequent and sought-after speaker at industry, corporate, educational, and technology events for his audience-designed, insightful, and energetic speeches.
Mike earned a bachelor's degree in computer science and management from Worcester Polytechnic Institute. While a student, Mike was awarded three U.S. patents for inventing an expert system used to train air traffic controllers around the world.
Senior Director of Product Management, SAP
Ashok is responsible for predictive analytics and machine learning for SAP HANA. Prior to his current role, Mr. Swaminathan led product management for several different products at Sybase, covering database technology, event processing, analytics for capital markets, data integration, replication, ETL, data auditing, and data archiving.
Mr. Swaminathan has proven leadership experience in the software industry, spanning all aspects of the software business, including product management, marketing, M&A, business development, and software engineering. Prior to SAP, Mr. Swaminathan held leadership roles at OnStation, Oracle, Booz Allen Hamilton, and Digital Equipment Corporation. In addition, Mr. Swaminathan cofounded a Web services start-up.
Mr. Swaminathan has a MBA from The Wharton School (Univ. of Pennsylvania), a master's degree in computer engineering from UMASS Amherst, and a bachelor's in electrical engineering from Indian Institute of Technology Madras.
Fern Halper, Ph.D.