The tracking and visualization of data flow from its origin through various transformations, processes, and systems to its final destination, providing complete transparency and traceability.
Data lineage is the process of understanding, recording, and visualizing data as it flows from data sources to consumption. It provides a complete audit trail showing where data originates, how it moves through different systems, what transformations are applied, and where it ultimately ends up being used for analysis or reporting.
Think of data lineage as a family tree for your data – it shows the relationships, dependencies, and transformations that occur as data moves through your organization's data ecosystem. This visibility is crucial for data governance, compliance, debugging, and building trust in your data and analytics.
Original systems where data is created or collected, including databases, APIs, files, and external feeds.
All processes that modify, clean, aggregate, or restructure data as it moves through the pipeline.
The paths and connections showing how data moves between different systems and processes.
Final locations where data is consumed, including reports, dashboards, ML models, and applications.
Relationships between data elements showing which downstream processes depend on upstream data.
Descriptive information about data structure, quality, ownership, and business context.
Meet regulatory requirements by providing complete audit trails and demonstrating data handling practices for GDPR, CCPA, and other regulations.
Quickly identify and resolve data quality issues by tracing problems back to their source and understanding impact downstream.
Understand the downstream effects of changes to data sources, schemas, or processes before making modifications.
Rapidly diagnose data issues by following the lineage trail to identify where problems originate and what systems are affected.
Shows the technical flow of data through systems, databases, and applications at the code and infrastructure level.
Focuses on business processes and how data supports business functions and decision-making workflows.
Tracks real-time data movement and transformations as they happen in production environments.
Focus on high-value, frequently-used data assets first
Use tools to automatically discover and maintain lineage
Add business meaning and ownership information
Regularly update lineage as systems and processes change
Provide easy-to-use interfaces for different user types
Embed lineage into daily data operations and processes
Anomaly AI provides complete data lineage transparency by default. Every insight, chart, and metric in your dashboards is directly traceable to its source data through SQL queries. You can see exactly how each number was calculated, what data was used, and verify the accuracy of every result – eliminating the black box problem common in AI analytics.
Get built-in data lineage with every analysis. See exactly how your insights are generated with full SQL transparency and source traceability.
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