Organizations without a quality scalable data foundation are often trapped in manual rule writing and management, limited data connectivity and a restricted view of data quality. This can result in significant productivity and revenue loss. And in pursuing today’s critical AI and ML initiatives where clean, accurate, reliable data is required, driving automation can help ensure you reach your goals faster. Join this session to learn how DataOps can help businesses deliver value faster and more efficiently by establishing predictable delivery and management of data pipelines.

In this session, we'll cover: DataOps, AI/ML, application workflow orchestration and data pipelines. Key Takeaways: In a recent survey about large enterprises' use of data management technology, 77% of respondents with mature DataOps programs reported their use of data has led to success in customer satisfaction initiatives, 57% reported that they're investing in technical data management tooling to drive data quality and integrity initiatives, and 53% are deriving business insights for new revenue opportunities.

* DataOps can make a powerful difference to any AI or data strategy by ensuring the people and processes involved are operating with agility and automation to deliver the most accurate, robust dataset.