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Paul Barth

Paul Barth

Dr. Paul Barth is the Global Head of Data Literacy for Qlik. Dr. Barth joined Qlik as CEO of Podium Data, which was acquired by Qlik in 2018 to create a next generation integrated data and analytics platform. He has spent decades developing advanced data and analytics solutions for Fortune 100 companies, and is a recognized thought-leader on business-driven data strategies and best practices. Prior to founding Podium Data, Paul co-founded NewVantage Partners, a boutique consultancy advising C-level executives at leading banking, investment, and insurance firms. Through his leadership roles at Schlumberger, Thinking Machines, Epsilon, Tessera, and iXL, Dr. Barth led the discovery and development of parallel processing and AI technologies to dramatically accelerate and simplify data management and analytics. Dr. Barth holds a Masters in Artificial Intelligence from Yale University, and a PhD in Parallel Computing from MIT.
Paul Barth

Paul Barth

Dr. Paul Barth is the Global Head of Data Literacy for Qlik. Dr. Barth joined Qlik as CEO of Podium Data, which was acquired by Qlik in 2018 to create a next generation integrated data and analytics platform. He has spent decades developing advanced data and analytics solutions for Fortune 100 companies, and is a recognized thought-leader on business-driven data strategies and best practices. Prior to founding Podium Data, Paul co-founded NewVantage Partners, a boutique consultancy advising C-level executives at leading banking, investment, and insurance firms. Through his leadership roles at Schlumberger, Thinking Machines, Epsilon, Tessera, and iXL, Dr. Barth led the discovery and development of parallel processing and AI technologies to dramatically accelerate and simplify data management and analytics. Dr. Barth holds a Masters in Artificial Intelligence from Yale University, and a PhD in Parallel Computing from MIT.
data literacy

Why Data Literacy is the Future of Work

Many questions remain in the aftermath of COVID-19, with some of the biggest ones relating to the economic recovery. When will the economy rebound and, if so, how long will it take? What skills are needed to ensure the next generation is capable of recovering from the next pandemic? And, are those skills applicable to other black swan events? It is equally as important to ask this question: What role will data play in not only predicting but preventing future problems? These are all important questions. But, we must reflect before we can use data to unlock a longer-term economic recovery.

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