Data Platforms Announces 2018 Conference and Online Virtual

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News Desk 2018
17
Data Platforms Announces 2018 Conference and Online Virtual Experience

SANTA CLARA, CA--(Marketwired - Aug 25, 2017) - Data Platforms , the first industry conference focused exclusively on helping data teams build modern, self-service big data platforms, today announced the dates for Data Platforms Live 2018 and Data Platforms Online 2017, a new virtual summit for data team leaders around the world.

Following a successful inaugural event, next year's Data Platforms Live 2018 will take place April 11-13 at the Wigwam Resort in Phoenix, Arizona. The conference provides a forum for professionals to network and collaborate across data-driven business strategies with industry peers in an intimate, educational environment. Attendees will have the opportunity to collaborate, share best practices and learn from industry-leading experts on how to create a modern big data platform.

"The opportunity for peer collaboration, best practice sharing and forming a community of expert data practitioners made Data Platforms 2017 a valuable investment for attendees," said David Hsieh, senior vice president of marketing, Qubole. "To further build on that success, Qubole is proud to be the presenting sponsor of Data Platforms Online , a virtual experience planned for September 19-22, 2017 that will bring the same kind of content to a wider community of data practitioners."

Data Platforms Online is a four-day virtual summit giving data team members from around the world the opportunity to join a community of peers to learn and share their industry expertise. The summit will feature exclusive access to Data Platforms event content. Attendees will receive practical lessons from leading industry experts about how to successfully scale big data operations, modernize data platforms and analytics architectures, and overcome many of the most significant challenges facing data teams today.

"Data Platforms 2017 provided a great sense of community for discussing best practices and project successes with other data practitioners," said Evan Harris , data scientist at Return Path. "The conference gathered a lot of like-minded people who are facing the same issues and all trying to solve the same problems. I came away with new knowledge about automating workflows and serverless computing that I can bring back to my company. I can't wait for next year's event."

"The best part of attending Data Platforms 2017 was the chance to network with other data practitioners in various industries and learn about the newest technologies and trends in big data. The conference exceeded my expectations," said Steve Gotlieb, data pipeline architect at Autodesk. "My favorite session was Qubole co-founder Joydeep Sen Sarma's talk on self-service data platforms and moving towards serverless architecture."

Highlights from the 2017 show included a keynote from R. David Edelman, former 'Geek-in-Chief' and advisor to President Barack Obama; a panel featuring visionaries from three of the most powerful cloud service providers -- Amazon Web Services, Microsoft and Oracle; and breakout sessions from leading data practitioners from Twitter, LinkedIn, Under Armour, Expedia and more.

Attendance for Data Platforms Live 2018 is limited to ensure peer collaboration, so save your spot today: www.dataplatforms.com .

About Qubole Qubole , the leading cloud-agnostic, big-data-as-a-service provider, is passionate about making data-driven insights easily accessible to anyone. Qubole is building the industry's first autonomous data platform. The cloud-based data platform, Qubole Data Service (QDS), removes the burden of maintaining infrastructure and enables customers to focus on their data. QDS is context-aware, self-managing, and self-learning to deliver unbeatable agility, flexibility and total cost of ownership. Qubole customers process nearly an exabyte of data every month. Qubole investors include CRV, Lightspeed Venture Partners, Norwest Venture Partners and IVP. For more information visit www.qubole.com

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