DataMasters

Data is critical to combating COVID-19. But stakeholders not being aligned around what they want to measure or what kind of outcomes are most helpful make data collecting challenging. That's the perspective of Paul Balas, who was previously the Chief Advisor. Advanced Analytics, at mining company Newmont. Paul is passionate about modeling information and is especially interested in how state and federal governments can better gather and share COVID-19 data.

Paul talked to us about how his analytics background gives him a unique perspective on the topic of COVID-19 data collection, how a people problem is contributing to the situation and how the private sector resolved similar data collection issues.

Ido Biger, CDO at El Al Israel Airlines, shares how embedding himself in different El Al departments made him a better leader, what practices he brought to the airline from his previous jobs, and what he teaches the next generation of data leaders as an adjunct lecturer.

Data ops has emerged as a way for organizations to better manage their data pipelines. You'll hear more about this concept from Chris Bergh, head chef, founder and CEO of DataKitchen, a software company that aims to help data professionals regain control of their data pipelines. He’ll talk about how his experiences in the software industry lead him down the data ops path, define what data ops is and why companies should give data ops a try.

What's required to master large numbers of data sources? First, avoid approaches that require writing rules. Then use machine learning and cloud computing to efficiently handle the workload. That advice comes from Mike Stonebraker, a database pioneer who helped create the INGRES relational database system, won the 2014 A.M. Turing Award and has co-founded several data management startups, including Tamr.

Mike, who's an adjunct professor of computer science at MIT, talks about common data mastering mistakes, why traditional tools aren't right for the task and shares examples of companies that have successfully mastered data at scale.

As vice president of data management and operations at Thomson Reuters, Marc Alvarez applies an entrepreneurial approach to data management. During his career, he’s found that treating data less like an IT project and more like a business asset requires fundamental changes around data management.

In this episode, Marc talks about what’s driving change around how companies use data, the role technologies like cloud computing and automation play in this shift and how organizations can get better business results from their data.

Success as a CDO increasingly means knowing how to use data to drive revenue. But at many organizations, data leaders are still figuring out how to work with their business counterparts. That's one takeaway from a survey of 300 C-suite executives on the topic of data and digital transformation. Conducted by NewVantage Partners since 2012, the survey includes the perspectives of leading Fortune 1000 companies including American Express, Capital One, Ford Motors, General Motors, Johnson & Johnson, Mastercard, and Met Life.

In this episode, Randy Bean, founder and CEO of NewVantage Partners, talks about the survey's results and looks at the overall state of the CDO. He discusses what makes a successful CDO, where the CDO should sit in an organization and why data initiatives need to be tied to business goals.

Once responsible for data governance, companies increasingly want CDOs who use data to drive the business. Someone who not only saw that evolution but experienced it is Mark Ramsey, who held the title of CDO when the role was very new.

Mark served as a data leader twice in his 30-year career. First as CDO at Samsung Mobile and then as Chief Data and Analytics Officer at GlaxoSmithKline. In this episode, Mark shares his thoughts on how the role has changed, what it’s like to be a company’s first CDO, and if a company’s reporting structure is a factor in a CDO’s success. And he’ll talk about how data is used in sports car racing, a sport he’s passionate about.

When you think about Hollywood, you probably think about movies, actors and scripts. But behind the scenes, tremendous amounts of data power a complex supply chain that shapes the movie trailers you watch and the release date of the next blockbuster.

In this episode of Datamasters, Eric Iverson, who was the CIO of Sony Pictures Television and CIO and CTO at top talent agency Creative Artists Agency, or CAA, shares how data powers the media and entertainment industry. He talks about how data is leveraged in television and movie production, the role data plays in television show distribution, and the data transformation that the entertainment industry went through in recent years.