Events
Events
Data Quality Lifecycle with MCP
Data Quality Lifecycle with MCP
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 Register today!
All Events
Data Quality Lifecycle with MCP
Data Quality Lifecycle with MCP
AI Agents for Data Quality: From Contracts to Anomaly Detection
AI Agents for Data Quality: From Contracts to Anomaly Detection
How to Implement Data Contracts in Production at Scale
How to Implement Data Contracts in Production at Scale
Closing the Data Quality Loop with AI Agents By Soda, Verified
Closing the Data Quality Loop with AI Agents By Soda, Verified
Closing the Data Quality Loop with AI Agents By Soda, Verified
Gartner Data & Analytics Summit, North America
Gartner Data & Analytics Summit, North America
How To Monitor Data Quality in a Databricks Unity Catalog
How To Monitor Data Quality in a Databricks Unity Catalog
Data Contracts and Data Testing in Modern Data Pipelines
Data Contracts and Data Testing in Modern Data Pipelines
Soda at Databricks Chicago
Soda at Databricks Chicago
Soda at Databricks NYC
Soda at Databricks NYC
Soda at Databricks Amsterdam
Soda at Databricks Amsterdam
Soda at Databricks London
Soda at Databricks London
Turn Collibra Policies into Automated Data Quality Checks with Soda
Turn Collibra Policies into Automated Data Quality Checks with Soda
Meet the World’s First Collaborative Data Contracts
Meet the World’s First Collaborative Data Contracts
The Fastest & Most Accurate Data Observability | Soda Live
The Fastest & Most Accurate Data Observability | Soda Live
Data Quality is Changing | Soda Live
Data Quality is Changing | Soda Live
How to Master Data Quality in Databricks | Soda Live
How to Master Data Quality in Databricks | Soda Live
How to Catch Data Issues Early in Databricks | Soda Live
How to Catch Data Issues Early in Databricks | Soda Live
How to Monitor Databricks Tables at Scale
How to Monitor Databricks Tables at Scale
Trusted by the world’s leading enterprises
Real stories from companies using Soda to keep their data reliable, accurate, and ready for action.
At the end of the day, we don’t want to be in there managing the checks, updating the checks, adding the checks. We just want to go and observe what’s happening, and that’s what Soda is enabling right now.
Sid Srivastava
Director of Data Governance, Quality and MLOps
Investing in data quality is key for cross-functional teams to make accurate, complete decisions with fewer risks and greater returns, using initiatives such as product thinking, data governance, and self-service platforms.
Mario Konschake
Director of Product-Data Platform
Soda has integrated seamlessly into our technology stack and given us the confidence to find, analyze, implement, and resolve data issues through a simple self-serve capability.
Sutaraj Dutta
Data Engineering Manager
Our goal was to deliver high-quality datasets in near real-time, ensuring dashboards reflect live data as it flows in. But beyond solving technical challenges, we wanted to spark a cultural shift - empowering the entire organization to make decisions grounded in accurate, timely data.
Gu Xie
Head of Data Engineering
4.4 of 5
Your data has problems.
Now they fix themselves.
Automated data quality, remediation, and management.
One platform, agents that do the work, you approve.
Trusted by
Trusted by the world’s leading enterprises
Real stories from companies using Soda to keep their data reliable, accurate, and ready for action.
At the end of the day, we don’t want to be in there managing the checks, updating the checks, adding the checks. We just want to go and observe what’s happening, and that’s what Soda is enabling right now.
Sid Srivastava
Director of Data Governance, Quality and MLOps
Investing in data quality is key for cross-functional teams to make accurate, complete decisions with fewer risks and greater returns, using initiatives such as product thinking, data governance, and self-service platforms.
Mario Konschake
Director of Product-Data Platform
Soda has integrated seamlessly into our technology stack and given us the confidence to find, analyze, implement, and resolve data issues through a simple self-serve capability.
Sutaraj Dutta
Data Engineering Manager
Our goal was to deliver high-quality datasets in near real-time, ensuring dashboards reflect live data as it flows in. But beyond solving technical challenges, we wanted to spark a cultural shift - empowering the entire organization to make decisions grounded in accurate, timely data.
Gu Xie
Head of Data Engineering
4.4 of 5
Your data has problems.
Now they fix themselves.
Automated data quality, remediation, and management.
One platform, agents that do the work, you approve.
Trusted by
Solutions
Trusted by the world’s leading enterprises
Real stories from companies using Soda to keep their data reliable, accurate, and ready for action.
At the end of the day, we don’t want to be in there managing the checks, updating the checks, adding the checks. We just want to go and observe what’s happening, and that’s what Soda is enabling right now.
Sid Srivastava
Director of Data Governance, Quality and MLOps
Investing in data quality is key for cross-functional teams to make accurate, complete decisions with fewer risks and greater returns, using initiatives such as product thinking, data governance, and self-service platforms.
Mario Konschake
Director of Product-Data Platform
Soda has integrated seamlessly into our technology stack and given us the confidence to find, analyze, implement, and resolve data issues through a simple self-serve capability.
Sutaraj Dutta
Data Engineering Manager
Our goal was to deliver high-quality datasets in near real-time, ensuring dashboards reflect live data as it flows in. But beyond solving technical challenges, we wanted to spark a cultural shift - empowering the entire organization to make decisions grounded in accurate, timely data.
Gu Xie
Head of Data Engineering
4.4 of 5
Your data has problems.
Now they fix themselves.
Automated data quality, remediation, and management.
One platform, agents that do the work, you approve.
Trusted by
Solutions