Automated Data Lineage
Data Governance
Key Benefits
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.
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.
Data quality issues often create ripple effects. Data lineage in Anomalo lets you view patterns and groupings involving multiple tables, helping speed up resolution.
FAQ
If you have additional questions, we are happy to answer them.
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. This comprehensive view promotes data democratization by making critical lineage insights accessible across the organization, empowering teams to make data-driven decisions with confidence.
Meet with our expert team and learn how Anomalo can help you achieve high data quality with less effort.