Data Quality Workflow with Soda MCP

Every data governance program lacks one and only one thing: Execution. Data stewards understand the standards but are never the ones who can enforce them. They know what "correct" means for your data better than anyone: ➤ order_id should never be null ➤ orders should land by 6am ➤ currency should be one of a fixed set of values ➤ revenue should never drop more than 20% day over day But knowledge and execution are two different things. To enforce any of it, someone has to write checks or tests, configure the monitor, wire it into the pipeline as a CI/CD gate, and deploy it. MCP unlocks this capability for all data management tasks. You can now connect an AI assistant to your pipelines and describe the various rules in plain language. The assistant maps it to the right tools - drafts the contract, configures the monitor, runs the check - and you can review and approve before anything deploys. Interested in getting started? Hakim is running the full data quality lifecycle live through MCP. He will explain how you can: ➤ Connect an AI assistant to your data quality tooling with MCP — and what that unlocks ➤ Go from an unmonitored dataset to an enforced data contract in minutes, through conversation ➤ Scale contract coverage across your estate