Understanding Data Governance: Challenges, Framework, and Practical Implementation

This article presents NetEase DataFang's insights on data governance, organized into three main parts: the problems data governance addresses, the governance framework, and practical implementation methods.

It identifies six key challenges that data governance solves: the disconnect between data development and governance, siloed "chimney" data development, lack of unified control across multiple platforms, insufficient quantifiable monitoring of governance processes, inadequate fine‑grained cost and value management, and the absence of a closed‑loop governance cycle.

The governance system is described as a full‑link framework built on actual enterprise and industry scenarios, leveraging data‑governance tools, processes, policies, and management to establish a comprehensive governance lifecycle.

Implementation focuses on integrating governance with development through a design‑first, standard‑first approach, covering overall solutions, metadata asset governance, lake‑out and lake‑in data governance, development standards, indicator management, data‑quality management, organizational structures, and long‑term operation and consolidation to ensure a sustainable governance loop.

The article concludes by emphasizing the need for continuous operation, monitoring, and improvement to maintain an effective data governance ecosystem.