Data Governance Manager for Master Data Hubs
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Solution Overview
Problem
Enterprises face challenges in maintaining accurate and up-to-date master data due to incomplete and erroneous information from operational and analytical systems, leading to data quality issues that are compounded by the increasing number of systems, and existing data governance tools fail to provide a streamlined process across all systems and hubs.
Innovation Solution
A data governance manager solution that unifies data governance functionality across operational, analytical, and master data hubs, allowing for the definition of common data quality rules, monitoring, and correction of data errors, while providing access to operational, analytical, and master data, and enabling compliance checking with pre-defined standards.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If separate data governance tools are used at each operational and analytical system and hub, then data quality monitoring can be performed locally, but data governance becomes compartmentalized and lacks streamlining across the enterprise
Solution Approach 1:
The patent combines multiple separate data governance tools into a single unified data governance solution that spans across operational systems, analytical systems, and master data hubs. This unified solution integrates data quality monitoring, data flow tracking, and data correction capabilities into one coherent platform, eliminating the compartmentalization issue while maintaining comprehensive data quality oversight throughout the enterprise.
Solution Approach 2:
The unified data governance solution provides multi-functional capabilities that can operate across different system types (operational, analytical, and master data hubs) through a common interface and rule set. The solution universally applies data quality rules, monitors data flows, and performs corrections across all systems, replacing the need for separate specialized tools at each location.
2Adaptability or versatility
If the number of operational and analytical systems is increased, then enterprise capabilities are enhanced, but data quality issues multiply
Solution Approach 1:
The unified data governance solution implements continuous feedback mechanisms that monitor data quality across all operational and analytical systems in real-time. When data quality issues are detected, the system automatically triggers correction processes and provides feedback to data sources, enabling continuous improvement of data quality as the enterprise expands its system portfolio.
Solution Approach 2:
The solution applies data quality rules and validation procedures before data is consolidated into master data hubs, performing preliminary cleansing and verification at the point of entry. This preventive approach ensures that data quality issues are addressed before they can propagate through multiple systems, maintaining reliability even as the enterprise adds more operational and analytical systems.
Data Source
AI summary
Improved data governance solutions to enterprise-level master data storage hubs are provided by implementing data governance functionality with regard to a master data hub. Data governance functionality is provided by providing visibility into the data quality the data of an enterprise.