Tencent Oula Data Governance Platform: Architecture, Practices, and Solutions

Oula is Tencent PCG's data governance platform launched in 2019. Built on DataOps principles, it offers a one‑stop solution for the full data lifecycle—production, management, governance, and usage—aiming to improve data governance maturity and create reliable, secure, and high‑quality data assets.

The platform consists of four core capabilities: data discovery, asset factory, metric platform, and governance engine.

Construction ideas and goals focus on industrializing data production and usage. Two typical scenarios are highlighted: (1) fixed business processes and a single compute‑storage technology stack, and (2) the need for multi‑technology solutions to handle complex, rapidly changing business requirements.

To cope with these scenarios, Oula emphasizes three core capabilities: efficient business‑process customization, efficient data‑model management, and a unified compute‑storage service.

The platform’s overall approach combines platform capabilities with governance projects, driven by four measures: data standards and alignment, full‑link metadata capability, unified data entities/models/services for "production‑as‑governance," and a governance evaluation system.

Data development governance follows a DataOps‑driven modeling platform. Common warehouse problems—metric inconsistency, data redundancy, and unclear metric sources—are addressed through standardized dimension modeling, visual modeling, DataOps workflow orchestration, unified metric management, and a knowledge‑graph‑based data map.

The unified metric tMetric aims to standardize metric modeling, management, certification, and ecosystem building. Its architecture defines metrics on top of various data sources, materializes them via scheduled jobs, and exposes them through a unified API for downstream consumption.

Data map and service construction builds a data fabric that lets users easily discover and use data. By automatically collecting metadata, the platform creates a knowledge network, enabling one‑click API generation for databases such as Redis, ClickHouse, and MySQL, with built‑in monitoring and auto‑scaling.

In the Q&A, the speakers explain how asset health scores are calculated across five dimensions (norms, security, quality, cost, and usage) and discuss data lineage storage, noting that while graph databases handle storage well, constructing complete lineage remains the main challenge.

Overall, the talk showcases Oula's end‑to‑end data governance practices, from platform construction and data development governance to unified metrics, data mapping, and service provisioning.