Inside Douyin’s Data Asset Platform: Transforming Data Lineage and Governance

Overview of Douyin’s Data Asset Management Platform

Douyin Group introduced a one‑stop data asset portal that goes beyond traditional metadata collection to provide systematic “manage, find, use” capabilities across its massive data ecosystem.

Key Goals of Data Lineage

Build full‑coverage, real‑time, accurate lineage to support downstream applications and improve platform efficiency.

Platform Architecture

The platform supports diverse data sources, collects metadata into a unified lake, and stores lineage in graph databases. It separates storage and query models to balance update speed and read performance.

Lineage Modeling

Three core entity types are defined:

DataStore – corresponds to tables.

Column – fields belonging to a DataStore.

Process – tasks that create relationships between entities.

These entities generate six relationship types, covering table‑level, column‑level, and task‑level lineage.

Metrics for Lineage Quality

Lineage quality score combines three primary indicators—coverage, accuracy, and completeness—into a weighted metric that reflects the overall health of the lineage data.

Applications

Lineage is applied in four major scenarios:

Data development – impact assessment, field‑level tracing, rapid task testing, change detection, and precise back‑trace.

Data governance – low‑value asset identification, cost calculation, timeliness and accuracy guarantees, and security risk detection.

Data assets – unified search, portal, recommendation, and AI‑driven search.

Data security – sensitive data propagation detection and protection.

Future Outlook

Douyin aims to standardize lineage, open it for community contribution, and achieve finer granularity such as row‑level lineage, further unlocking value for quality, efficiency, and security.