Data Governance Practices and Platform Construction with Alibaba DataWorks

Alibaba treats data as a core asset and has evolved its data platform from fragmented analysis to a unified, intelligent system. The DataWorks team presents their experience in addressing new data governance challenges such as cost reduction, stability, efficiency, risk control, and security.

Data Prosperity Benefits and Challenges

Massive data volumes (e.g., MaxCompute processing 2.79 EB on Double‑11 2021) and millions of daily tasks demonstrate the platform’s scale. However, the real value depends on user adoption across engineers, analysts, operations, finance, and HR, requiring broader user engagement and efficient data usage.

Four Governance Stages

Start Stage : Ensure data exists and is produced reliably; address cluster resource shortages and task failures.

Application Stage : Promote data democratization while maintaining efficiency as user numbers grow.

Scale Stage : Manage data security and risk as data applications proliferate.

Mature Stage : Focus on cost governance while sustaining business agility.

Key Governance Issues

Insufficient data stability (task failures, resource bottlenecks).

Low data‑use efficiency (hard to find or understand data).

High data‑management risk (leakage, compliance).

Rising data costs (over‑provisioned resources, redundant tables).

DataWorks Solutions

The platform provides a full‑link governance suite:

Data Modeling & Standards : Online data‑model committees, model lifecycle management, and automatic lineage.

Intelligent Baseline & Scheduling : Baseline configuration, predictive alerts, resource prioritization for critical tasks.

Quality Governance : Pre‑, mid‑, and post‑process quality checks, automated rule generation, and multi‑role collaboration.

Application Efficiency : Data map for metadata discovery, unified SQL editor with auto‑completion, visual query building, and open APIs for custom services.

Security Governance : Role‑based access, data classification & masking, AI‑driven risk behavior detection, and compliance with national standards (DSMM).

Cost Governance : Elastic CU for MaxCompute, unified storage‑compute architecture with Hologres, and health‑score driven optimization across storage, compute, and platform layers.

Organization & Culture

Alibaba’s governance structure includes a Data Professional Committee, specialized governance task forces, and dedicated governance teams. Practices such as training, competitions, health‑score metrics, and regular audits embed data governance into daily operations and promote continuous improvement.

Impact & Adoption

DataWorks serves all Alibaba business units (Taobao, Tmall, Youku, etc.) and over 10,000 external customers across industries, delivering improvements such as 30 % cost reduction, 64 % increase in core‑table usage, and millions of daily API calls.

Future Trends

Strengthening data‑ownership regulations.

Integrating governance into development (DataOps).

Automating metadata discovery, classification, and policy enforcement.