The Future of DataOps: the Tie That Binds XOps, Illuminated at DataOps Summit 2021

The future of analytics must include a modern data integration platform delivering continuous data to every Ops discipline

SAN FRANCISCO--(BUSINESS WIRE)--StreamSets, provider of the industry’s first DataOps platform, today details its vision for the future of DataOps with the premier professional conference DataOps Summit 2021. With a recent Honorable Mention in the 2021 Gartner^® Magic Quadrant™ for Data Integration Tools¹, StreamSets believes it is driving the continued maturation of the discipline by gathering data professionals across the industry to exchange ideas around data and data practices.

The Future of Data: DataOps As a Force Multiplier
DataOps Summit explores the future of data in a tumultuous landscape. As the pace of change in data-oriented disciplines accelerates, the adoption of operationalization tactics across disciplines is also accelerating. Practices such as AI and ML are adopting DevOps principles of automation and monitoring, to gain agility, enhance collaboration, break down silos and more. These principles create harmony between business, development and operations.

Likewise, DataOps tames data chaos and delivers it to all XOps disciplines. “DataOps is the force multiplier for the effectiveness of machine learning and MLOps,” said Girish Pancha, CEO of StreamSets. “And it’s the same with any Ops discipline. You’ll find all of them need DataOps. DevOps needs data pipelines; CloudOps needs migration pipelines; PrivacyOps needs data protection pipelines; SecOps needs edge pipelines. DataOps is that which binds all of XOps.”

The key drivers behind XOps are highlighted in Pancha’s keynote, ‘The Future of Data,’ at DataOps Summit 2021 today (virtual and worldwide). The session outlines the three principles behind DataOps, including the one responsible for driving data innovation and digital transformation in an organization.

Customer Adoption on the Rise
During DataOps Summit, companies from Humana to Playstation and partners from Axis to Cleverbits will discuss their DataOps practices and deployments. Many of their sessions will discuss the active role StreamSets’ DataOps Platform plays and how it bolsters their DataOps practices by addressing data drift — the unpredictable, unannounced and unending changes to data — and providing complete data observability.

"Axis Group is driven to make a positive impact on the world by helping people at all levels solve their biggest problems with analytic solutions. The DataOps capabilities that we have and that we've built with partners such as StreamSets are integral to these solutions," said Scott Reedy, Executive Vice President of Consulting at Axis Group. “We are proud to partner with StreamSets to bring best-of-breed solutions to our customers complemented by the thought leadership that they bring to the domain of DataOps.”

To learn more about DataOps, register for the StreamSets DataOps Summit 2021 or visit the StreamSets website.

¹ Gartner does not endorse any vendor, product or service depicted in its research publications, and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner research publications consist of the opinions of Gartner’s research organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose.

About StreamSets
At StreamSets, our mission is to make data engineering teams wildly successful. Only StreamSets offers a platform dedicated to building the smart data pipelines needed to power DataOps across hybrid and multi-cloud architectures. That’s why the largest companies in the world trust StreamSets to power millions of data pipelines for modern analytics, AI/ML and smart applications. With StreamSets, data engineers spend less time fixing and more time doing. To learn more, visit www.streamsets.com and follow us on LinkedIn.

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