Level: Beginner to Intermediate

Prerequisite: None

Deanne Larson, Ph.D., DM, CBIP

President

Larson & Associates and TDWI Fellow

DataOps is a process-focused and automated methodology for delivering data for machine learning and AI that concentrates on reducing cycle time and improving the quality of advanced analytics deliverables. DataOps builds on the concepts of DevOps, continuous integration and delivery (CI/CD), and agile. These concepts support quick and efficient software delivery, but analytics is more than software—it is also about the delivery of insights. DataOps needs to deliver consistent and meaningful data which means automating the data lifecycle of acquisition, understanding, integration, transformation, and deployment. This course will address best practices that contribute to consistent and automated analytics results.

You Will Learn

• The value of DataOps
• Agile and DevOps principles applied to DataOps
• The scope and components of DataOps
• Where CI/CD is applied in DataOps
• Best practices and how to get started

Geared To

• Project managers
• Data scientists
• Data engineers
• Analysts
• Analytics managers