Automated Data Lineage Tools

Streamline transparency and governance by viewing data quality in the context of how data flows from source to destination.

Trusted by Industry Leaders

Data lineage helps you triage and resolve data quality issues

Get a clear, visual representation of how your data flows to pinpoint the cause and effect of any issues

• View data quality checks alongside lineage
• Find the source of data issues upstream
• Easy for everyone, API or no-code configuration
• See how data quality impacts downstream consumers

Data Governance

Improve data management by ensuring quality at every step in the data lifecycle

Verify the entire data flow for end-to-end governance and compliance

• Increase data discovery and literacy by exposing source and destination tables
• Identify upstream tables where you may need to add monitoring
• Verify that quality checks are in place across your most essential data flows

Key Benefits

Automated Data Lineage Tools

End-to-end data mapping

Data quality matters along the entire journey from source to destination. With lineage, you can view the complete lifecycle of your data assets and jump into any table to see its checks in Anomalo.

Faster, more informed triage

Escalate data quality issues appropriately by jumping from Anomalo’s real-time notifications to the table lineage view, which provides a clear understanding of how downstream consumers are impacted.

Cluster issues and identify the root cause

Data quality issues often create ripple effects. Data lineage in Anomalo lets you view patterns and groupings involving multiple tables, helping speed up resolution.

Frequently Asked Questions

How does Anomalo's automated data lineage tool discover and map the data lineage information automatically?

Anomalo uses the feature from the data warehouse to query the lineage and stores these features in our production database.

What data sources and what parts of the data stack does Anomalo support with lineage?

Anomalo supports data lineage for Databricks, Snowflake, and BigQuery. Our approach solely relies on database records, thus excluding steps such as transformations in Airflow from consideration in our data lineage tracking process.

How often does data lineage tracking occur in the Anomalo UI?

To ensure cost efficiency for your deployment, we fetch lineage information from the data warehouse once per day. However, if you need fresher lineage information, you can trigger a refresh manually from the Admin menu in Anomalo.

What is the user experience like for viewing data lineage in Anomalo?

You can zoom in and out and pan the screen to see how data flows within the data environment. For each data source, you can look at data quality information like which checks have passed or failed in Anomalo, right alongside the lineage data.

What makes Anomalo one of the best data lineage tools?

Anomalo is considered a top data lineage tool due to its seamless integration of data lineage and quality checks in one platform. It provides a clear, visual representation of data flow, helping users quickly identify and resolve data quality issues. The tool supports end-to-end data mapping, allowing for faster triage and root cause analysis. It is user-friendly, with both API and no-code configurations, and supports major data warehouses like Databricks, Snowflake, and BigQuery.

How do Anomalo's data lineage tools support data teams in ensuring data accuracy?

Anomalo’s data lineage focuses on providing transparency across data pipelines, enabling data teams to trace the flow of information and identify potential issues that could impact data accuracy.