Workday has a strong partnership with Databricks, Inc. (Databricks) and currently utilizes their tools to build, test, and evaluate machine learning (ML) use cases in Innovation Services. Workday has added Databricks, Inc. as a new subprocessor for Workday Peakon Employee Voice (Peakon) as a provider of tools to build, test, and evaluate machine learning (ML) use cases. Databricks will process Peakon Data contributed to Workday’s Machine Learning Developments (MLDE) in both the United States and the European Union. The primary reason for this decision is to decrease the time to market for Workday’s ML features and functionality and to improve their efficiency and personalization. Databricks’ capabilities align with Workday’s best-in-class security and privacy commitments, and support Workday’s needs around innovation, growth, and scalability:
- Productivity and efficiency: A robust data analytics platform to build, test, and evaluate ML use cases. It also helps maintain and update ML products and features; and track all ML model experiments in a standardized manner.
- Data security and privacy: World class end-to-end platform security and privacy commitments for data and users.
- Scalability: Workday data scientists and engineers can analyze large sets of data to streamline the building, testing, and evaluation of our ML products and use cases.
What Does This Mean for You?
There’s no required action for you to take to gain the benefit of Workday’s improved ML process. Workday will use Databricks tools to temporarily process Peakon data in the same region as MLDE where persistent storage of Peakon data will remain.
Peakon data won’t persist in any of Databricks' hosted cloud. Databricks might persist system logs associated with management of Spark clusters or with other tooling they provide as part of their platform. The logs won’t include any customer information and these logs get stored and encrypted at rest. Databricks personnel don’t have access to any Peakon data.