According to Google developers, "Only a small fraction of real-world ML systems are composed of the ML code. The required surrounding infrastructure is vast and complex." By focusing on DataOps your teams will be able to deliver faster, with higher quality, using the tools that they love. The topics covered will include:
- Data science challenges and DataOps definitions.
- The four As of DataOps
- Automate and monitor pipelines
- Automate deployments
- Automate and monitor quality
- Automate sandboxes
