Ascend.io, the Data Automation Cloud, announced the industry’s first annual Data Automation Summit, taking place virtually April 13-14, 2022. The Data Automation Summit will provide a unique opportunity for data professionals and data leaders to engage with peers and learn more about the use of automation across the data lifecycle to increase team productivity and accelerate the creation of critical data products.
With a heightened focus on transformative automation technologies, speakers and presenters will share real-life use cases, tactical and tangible best practices, and live Q&As. The initial keynote speakers include Sean Knapp, CEO and founder of Ascend.io; and DJ Patil, former U.S. chief data scientist. As one of the most renowned and influential data scientists in the world, Patil’s strategic efforts transformed the U.S. Federal Government into a data-driven enterprise, while also instituting 40 chief data officer roles.
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“Data teams are facing huge amounts of pressure to increase output and deliver more insights for the business. While this paradigm won’t slow down any time soon, automation holds the potential to give data teams more leverage and flexibility to meet the demands of their business,” said Sean Knapp, founder and CEO of Ascend.io. “As the data ecosystem continues to expand, the breadth of capabilities data teams need to automate is virtually endless. During this year’s first annual Data Automation Summit, we’re thrilled to accelerate the automation conversation among data professionals and showcase how some of today’s most innovative companies are using advanced approaches to automation to create highly sophisticated data platforms and products.”
Additional sessions include curated conversations, case studies, panel discussions, and more from a variety of data engineers, data analysts, data architects, and chief data officers discussing topics including:
- How automation technologies accelerate data workloads
- Bringing data meshes from concept to reality
- Best practices for lessening maintenance burdens with data pipeline automation
- Intelligently unifying data and analytics engineering with data automation technologies
- And more
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