Bill Schmarzo

Bill Schmarzo

CIO

Country: United States

Keynote Speaker

Bio

Bill Schmarzo, author of “Big Data: Understanding How Data Powers Big Business” and “Big Data MBA: Driving Business Strategies with Data Science”, is CIO at Hitachi Vantara.  As Hitachi Vantara CIO, Bill guides the technology strategy for IoT and Analytics. With his breadth of experience delivering advanced analytics solutions, Bill brings a balanced approach regarding data and analytic capabilities that drive business and operational outcomes. 

He’s written white papers, is an avid blogger and is a frequent speaker on the use of Big Data and data science to power an organization’s key business initiatives.  He is a University of San Francisco School of Management (SOM) Executive Fellow where he teaches the “Big Data MBA” course. Bill also just completed a research paper on “Determining The Economic Value of Data”.  Bill is also an Honorary Professor within School of Business and Economics at the National University of Ireland-Galway.

Bill has over three decades of experience in data warehousing, BI and analytics.  Bill authored the Vision Workshop methodology that links an organization’s strategic business initiatives with their supporting data and analytic requirements. Bill serves on the City of San Jose’s Technology Innovation Board, and on the faculties of The Data Warehouse Institute and Strata.

Bill’s background includes CTO at Dell EMC and VP of Analytics at Yahoo. He was recently named the #4 Big Data influencer, #4 Data Science and #6 Digital Transformation influencer worldwide by Onalytica.

Bill holds a Masters Business Administration from University of Iowa and a Bachelor of Science degree in Mathematics, Computer Science and Business Administration from Coe College.

Presentation

Exploiting the Economic Value of Your Data

Most organizations lack a methodology for determining the economic value of their data and analytics. But Data and Analytics are unique economic assets that not only never wear out, but they actually can appreciate, not depreciate, in value the more valuable they are used. Learn how your organization can embrace a systematic approach to build out your data and analytic economic assets one use case at a time.

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