When it comes to data analytics, you don’t want to know “how the sausage is made.” The state of most data analytics pipelines is deplorable. There are too many steps; too little automation and orchestration; minimal reuse of code and data; and a lack of coordination between stakeholders in business, IT, and operations. The result is poor quality data delivered too late to meet business needs.
DataOps is an emerging approach for building data pipelines and solutions. This session will explore trends in DataOps adoption, challenges that organizations face in implementing DataOps, and best practices in building modern data pipelines. It will examine how leading-edge organizations are using DataOps to increase agility, reduce cycle times, and minimize data defects, giving developers and business users greater confidence in analytic output.
You will learn:
- What is DataOps and why you need it
- The dimensions of DataOps
- The state of DataOps adoption
- DataOps best practices and challenges