Migrate your data, not your data quality issues
Automate reconciliation and validation to ensure complete, trusted data during migrations.
Trusted by
Verify source and target match during and after migration
Run reconciliation checks on row counts, values, and records. Detect duplicates, missing data, or schema mapping errors before production cutover.
Automate validation across every stage
Integrate reconciliation and validation checks directly into CI/CD workflows and data pipelines to automate quality assurance throughout the migration lifecycle.
Prevent quality issues from migrating forward
Profile your source data to identify issues early. Establish baseline checks so only clean, validated data moves to your new platform.
Verify source and target match during and after migration
Run reconciliation checks on row counts, values, and records. Detect duplicates, missing data, or schema mapping errors before production cutover.
Automate validation across every stage
Integrate reconciliation and validation checks directly into CI/CD workflows and data pipelines to automate quality assurance throughout the migration lifecycle.
Prevent quality issues from migrating forward
Profile your source data to identify issues early. Establish baseline checks so only clean, validated data moves to your new platform.
Verify source and target match during and after migration
Run reconciliation checks on row counts, values, and records. Detect duplicates, missing data, or schema mapping errors before production cutover.
Automate validation across every stage
Integrate reconciliation and validation checks directly into CI/CD workflows and data pipelines to automate quality assurance throughout the migration lifecycle.
Prevent quality issues from migrating forward
Profile your source data to identify issues early. Establish baseline checks so only clean, validated data moves to your new platform.
Why data teams choose Soda to support their data migrations
Soda's data reconciliation, quality testing, and monitoring capabilities ensure data trust at each stage of your migration: from initial planning through production deployment.
Reconciliation Checks
Reconcile source and target datasets
During migration, detect issues such as duplicate runs, missing batches, or incomplete transfers.Optimize compute: start with aggregate-level checks (row counts, sums, averages), then apply targeted row-level validation (missing records, value mismatches, duplicates) for high-priority datasets.
Reconciliation Checks
Reconcile source and target datasets
During migration, detect issues such as duplicate runs, missing batches, or incomplete transfers.Optimize compute: start with aggregate-level checks (row counts, sums, averages), then apply targeted row-level validation (missing records, value mismatches, duplicates) for high-priority datasets.
Reconciliation Checks
Reconcile source and target datasets
During migration, detect issues such as duplicate runs, missing batches, or incomplete transfers.Optimize compute: start with aggregate-level checks (row counts, sums, averages), then apply targeted row-level validation (missing records, value mismatches, duplicates) for high-priority datasets.
Pipeline Testing
Stop migration failures before production
Integrate Soda's pipeline testing directly into your ETL and CI/CD workflows with native support for Airflow, Dagster, Prefect, and dbt. Every migration batch runs through automated reconciliation checks.
Pipeline Testing
Stop migration failures before production
Integrate Soda's pipeline testing directly into your ETL and CI/CD workflows with native support for Airflow, Dagster, Prefect, and dbt. Every migration batch runs through automated reconciliation checks.
Pipeline Testing
Stop migration failures before production
Integrate Soda's pipeline testing directly into your ETL and CI/CD workflows with native support for Airflow, Dagster, Prefect, and dbt. Every migration batch runs through automated reconciliation checks.
Collaborative Data Contracts
Ensure new and legacy systems agree on data quality standards
Define data contracts between source and target systems.Use Soda's data contracts to formalize expectations for row counts, column values, and key business metrics. During parallel runs, validate that both environments meet shared standards.
Collaborative Data Contracts
Ensure new and legacy systems agree on data quality standards
Define data contracts between source and target systems.Use Soda's data contracts to formalize expectations for row counts, column values, and key business metrics. During parallel runs, validate that both environments meet shared standards.
Collaborative Data Contracts
Ensure new and legacy systems agree on data quality standards
Define data contracts between source and target systems.Use Soda's data contracts to formalize expectations for row counts, column values, and key business metrics. During parallel runs, validate that both environments meet shared standards.
Smart Alerting
Detect reconciliation failures the moment they happen
When reconciliation checks fail or data patterns deviate from expected norms, your team receives instant alerts to investigate and address root causes.
Smart Alerting
Detect reconciliation failures the moment they happen
When reconciliation checks fail or data patterns deviate from expected norms, your team receives instant alerts to investigate and address root causes.
Smart Alerting
Detect reconciliation failures the moment they happen
When reconciliation checks fail or data patterns deviate from expected norms, your team receives instant alerts to investigate and address root causes.
Case studies
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
Start trusting your data. Today.
Find, understand, and fix any data quality issue in seconds.
From table to record-level.
Trusted by
Case studies
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
Start trusting your data. Today.
Find, understand, and fix any data quality issue in seconds.
From table to record-level.
Trusted by
Solutions
Case studies
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
Start trusting your data. Today.
Find, understand, and fix any data quality issue in seconds.
From table to record-level.
Trusted by
Solutions
Company