What Ant Group Learned: 5 Pillars of Effective Data Governance

Reading Guide: This article shares Ant Group's experience in big data governance.

Main sections:

Data Governance Overview

Data Quality Governance

Data Storage Governance

Future Thoughts on Data Governance

Data Governance Overview

Industry definitions vary, but Ant focuses on five critical aspects for enterprise operation: architecture, security, compliance, quality, and value.

Why these five aspects?

First, ensure data flow and usability while meeting regulatory requirements such as user privacy and anti‑money‑laundering, guaranteeing compliance and security across environments.

Second, deliver data to business without errors or delays, addressing data quality so that business can trust the data.

Third, support collaborative development in big data by planning and governing data architecture, including model design, standards, and master data, to make data reusable and usable.

Finally, treat data as a closed‑loop ecosystem where the process from acquisition to processing to business enablement is sustainable, emphasizing both negative value (costs of computation, storage, assets) and positive business value generated by data consumption.

This sharing focuses on two topics: data quality governance and storage governance, which will be introduced next.

Source: Excerpt from “A Plain Big Data e‑Book”, Chapter 1. Scan the QR code to download the full e‑book.