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Industry SolutionsFortune 500 Enterprise Data Asset Management Project
The client had established basic master data governance through MDM system implementation, but lacked:
Enterprise-wide data asset inventory
Systematic operational measures
Unified management tools
resulting in ineffective control by the digital center
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01
Data quality issues are resolved within individual project teams, lacking a unified management mechanism.
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02
The absence of effective data standards leads to siloed system development across different business units.
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03
The absence of effective data standards leads to siloed system development across different business units.
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04
While master data management guidelines have been issued at the group level, they are limited in scope and fail to achieve comprehensive domain coverage.
GienTech helps enterprises build a holistic data asset management system at the group level. This includes a three-tier organizational structure and eight supporting data governance policies, laying the foundation for unified data asset management across the group and its subsidiaries—covering data standards, data quality, and data lake governance.
Conducted a full inventory of data assets across 25 systems under four key domains: Human Resources, Finance, Risk Control, and Master Data. The inventory includes metadata, KPIs, data metrics, and data service interfaces.
Deployed a data asset operations platform that connects metadata from all domains and maps the inventoried assets into a centralized data catalog. This platform enables key functions such as data asset registration, publishing, subscription, certification, viewing, and usage. Based on hierarchical classification standards, the catalog supports enterprise-wide access, request, and application of data assets.
• Taking data asset inventory as the entry point, the project conducts full-domain mapping at the metadata level to establish a comprehensive data asset catalog for the group.
• Under strict security and compliance requirements, it enables data asset registration, usage, tracking, viewing, and evaluation.
• The initiative builds a comprehensive data asset operations framework, continuously enhancing data consumers' capabilities and improving the enterprise’s data management and application maturity—laying a solid foundation for digital transformation.
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