How to Build an Effective Data Asset Management Framework for Enterprises

Introduction

Enterprise data asset management requires a data asset framework to support the display, recording, and analysis of data assets. The framework clarifies the data assets an organization owns, enables secure sharing, improves data quality, and facilitates data monetization.

Key Components

Data Asset Catalog Management is essential for effective management of enterprise data assets.

Policy Support

In the banking industry, national and regulatory policies released between 2020 and 2021 define data as a production factor and provide guidance for data governance, illustrating strong policy support for data asset management.

Enterprise Demand

From an enterprise perspective, data assets form the solid foundation for digital transformation and digital operations, linking industry analysis, strategic vision, concrete measures, and planning.

Development Trends

Data asset management is becoming a major trend in data management, shifting focus from traditional data handling to data value creation.

Data asset management drives the transformation of data work toward value conversion.

Assetization and management concepts promote the conversion of data management into data value.

A data‑asset‑oriented approach links metadata, standards, models, quality, and security, guiding business value realization.

Customer‑centric, value‑driven services enable efficient data asset services and analytics.

Three Aspects of Data Asset Management

Management perspective, management functions, and organizational system.

Data Asset Catalog System

The catalog provides a classification method for enterprise data resources.

Data Tags and Asset Relationship

Data tags form a networked classification for data assets, allowing categorization, grading, and additional management attributes, and enabling fast retrieval through a data management platform.

Catalog Management and Application Scenarios

Catalog management includes maintenance and security permission management. Application scenarios cover data asset visualization, catalog services, and data analysis.

Case Study: Financial Company

The case outlines six construction steps:

Asset inventory (data asset inventory and information completion).

Framework design (business perspective, industry models, best practices, business standards).

Data tag design (classification, sharing, responsibility, masking, quality, processes, entities).

Asset‑catalog association.

Asset tagging (creating a networked retrieval system).

Platform management.

Construction Path

Step 1: Build the path; Step 2: Construct the catalog; Step 3: Implement the platform.