Building Integrated Data Governance and R&D Operations with DataOps: Practices and Insights from China Unicom Digital Technology

China Unicom Digital Technology presents a comprehensive overview of its DataOps practice, describing how the organization integrates data governance, research and development, and operational processes into a unified capability.

The discussion begins with the difficulties and challenges of DataOps implementation, including tool integration, complex data distribution, governance timing, and the increasing difficulty of data usage due to emerging AI and large‑model technologies.

Three key reflections are offered: the distinction between data and software development, strategies for continuous capability improvement, and the fusion of innovative technologies such as AI and blockchain into the DataOps ecosystem.

A seven‑step “Innovative Data Governance” methodology is introduced, covering scenario clarification, data identification, source recognition, governance, aggregation, usage, and quality improvement, forming a closed‑loop for data R&D, delivery, operation, and maintenance.

The article details a multi‑center collaborative mechanism built around eight core centers—security, standards, development, scheduling, quality, assets, applications, and operations—each providing specific governance, platform, and service functions to enhance data quality, security, and operational efficiency.

Finally, the piece summarizes the sustainable operation model, the data flywheel effect, and the transformation from data management to rapid business value generation, emphasizing collaboration, empowerment, and continuous improvement.