Data Governance Practices and Product Perspective at Beike Zhaofang

Data Governance Purpose and Content – Data governance aims to increase the value of data by improving sharing, accuracy, and usability, enabling better user services and more efficient business management. The article outlines three directions: data sharing, data accuracy, and data usability.

Focusing Governance Scope on Company Characteristics – Beike’s data systems are middle‑platform oriented, requiring centralized data flow for front‑end applications, real‑time operations, and risk control. Governance concentrates on data convergence and efficiency improvements to reduce communication costs and support high‑frequency data needs.

Middle‑Platform Practice: Construction Content and Approach – The platform builds capabilities for data production, publishing, testing, subscription, and quality monitoring. It categorizes data entities (APIs, events, metrics, tables) into domain modules, supports configurable development, unified format standards, self‑service testing, and automated alerts.

Project Goal Management – Goals include data discoverability, completeness of core field information, and reduction of bad cases. Success is measured by data demand fulfillment rates, field completeness, and quality metrics.

Product and Operation Experience – Successful practices involve early user feedback, deep requirement digging through interviews, and driving adoption by solving core pain points such as data format unification. The governance team embeds within business to understand real needs.

Challenges and Measures – Governance requires strategic support, cross‑team collaboration (security, legal), and continuous iteration of standards. Emphasis is placed on respecting users, incremental documentation, building business dictionaries, and leveraging both top‑down and bottom‑up promotion to enhance data value.