LogoLogo
  • Introduction
    • Overview
    • Why Alvin?
    • Connect your systems
      • Data Warehouse
        • BigQuery
          • Provision source system credentials
          • Provision with GCloud CLI
        • Snowflake
        • Databricks
      • Business Intelligence
        • Looker
      • Orchestration
        • dbt
      • SSO (Single Sign-On)
    • Security & compliance
    • Types of metadata
    • FAQ
  • Cost Monitoring
    • Introduction to Cost Monitoring
    • Compute
    • Storage
  • BI Query Optimizer
    • Introduction to Query Optimizer
    • How does it work?
    • Getting started
  • Workflow automation
    • Introduction to Workflow Automation
    • Events definitions
    • Configuring Workflows
  • Anomaly Detection
    • Anomaly Detection
  • Exploring Metadata
    • Lineage
      • Depth of lineage
    • Impact Analysis
    • Entities
    • Entity View
    • Metadata Warehouse
Powered by GitBook
On this page
  1. Exploring Metadata

Lineage

PreviousAnomaly DetectionNextDepth of lineage

Last updated 8 months ago

Alvin's lineage is one of the things that sets us apart. The lineage is layered, meaning that you can add different types of overlays, like for data lineage. This is useful for many cases - for instance the historical row count layer can be a quick way to investigate any anomalies upstream of a table with off-putting row counts.

In addition to this, there is built in functionality to "skip" entities in the graph, while still showing the lineage - let's say you don't want to see Looker Explores, but you still want to see the lineage between a table and a dashboard!

Google maps
Use the controls to define what entities you want to see, and how much up/downstream
Add volume and usage statistics
Click a job node to View the Query details