AWS Clean Rooms announces support for parameters in PySpark analysis templates, offering increased flexibility for organizations and their partners to scale their privacy-enhanced data collaboration use cases. With this launch, you can create a single PySpark analysis template that allows different values to be provided by the Clean Rooms collaborator running a job at submission time without modifying the template code. With parameters in PySpark analysis templates, the code author creates a PySpark template with parameters support, and if approved to run, the job runner submits parameter values directly to the PySpark job. For example, a measurement company running attribution analysis for advertising campaigns can input time windows and geographic regions dynamically to surface insights that drive campaign optimizations and media planning accelerating time-to-insights.
With AWS Clean Rooms, customers can create a secure data clean room in minutes and collaborate with any company on AWS or Snowflake to generate unique insights about advertising campaigns, investment decisions, and research and development. For more information about the AWS Regions where AWS Clean Rooms is available, see the AWS Regions table. To learn more about collaborating with AWS Clean Rooms, visit AWS Clean Rooms.
Categories: general:products/aws-clean-rooms,marketing:marchitecture/analytics
Source: Amazon Web Services
Latest Posts
- Amazon RDS for MySQL now supports new minor version 8.4.11
- Amazon Redshift now supports concurrency scaling of streaming ingestion workloads from Amazon Kinesis data streams
- MC1459141: Microsoft Teams Adds Admin Policy to Automatically Block External Meeting Bots
- MC1411574: Microsoft Entra ID Applies System-Preferred Authentication to First-Factor Sign-In
