Bill Schmarzo - The dean of Big Data in the Data Science and AI Industry

This new English series of the Data Stand-up! podcast will be full of interesting guests and respected professional from the Data and AI Industry.

This weekend Jesús calls Bill Schmarzo, “Dean of Big Data”, a pragmatic hands-on influencer and innovator. Bill has been recognised as an industry leader in Big Data, Data Science, Design Thinking and Data Monetisation. In the past he was Chief Innovation Officer at Hitachi Vantara and Chief Technology Officer at EMC.

He has written 4 books “Big Data: Understanding How Data Powers Big Business,” “Big Data MBA: Driving Business Strategies with Data Science” and the forthcoming “Economics of Data, Analytics and Digital Transformation;” and published over 350 industry-leading articles and educational videos on the application of Big Data, Data Science, AI / ML and IoT to drive data monetisation and digital transformation.

He is also a Professor an has developed and taught the “Big Data MBA”, a course for integrating data and analytics into the operations of the business, at the University of San Francisco School of Management and at the National University of Ireland-Galway School of Business & Economics. He also lectures to numerous universities and organisations worldwide.

The Value Engineering methodology, which he created, drives customer collaboration (co-creation) and organisational alignment in identifying, validating, valuing and prioritising the organisation’s most important business use cases where data and analytics can have tangible and measure impact. For this he integrates Design Thinking with Data Science while employing a “Rapid exploration, rapid testing, failure-empowering, continuously-learning”  development methodology.

We briefly introduce with Bill the business-first approach mechanisms for establishing, nurturing, empowering and leveraging  Advanced Analytics, Data Science and Value Engineering teams in order to uncover the customer, product and operational insights buried in each organisation’s data.

Click play if you are keen to learn how to drive data monetisation.