DataOps promises to accelerate the process of creating and modifying data pipelines while simultaneously improving quality. DataOps will turn what has historically been a hand-crafted discipline into a lights-out, automated data environment that speeds delivery, improves customer satisfaction, and generates business value.
But DataOps is a big tent that borrows principles from DevOps, Lean, Agile, and Total Quality Management methodologies. And while DataOps is focused on repeatable operational processes, there is the corresponding automation technology that is helping accelerate many of these processes. The challenge is absorbing these new processes and new technology while the underlying execution ( Hadoop, Spark, Databricks etc.) and storage (hdfs, S3, ADLS, etc) environments are rapidly evolving and companies are migrating to the cloud(s). Most companies don’t know where to start. This session will define DataOps, discuss its benefits and challenges, and offer best practices for how to proceed.WEBCAST