What's In / What's Out for Data Quality
A recent report from Enterprise Data Management Council from "What's In and What's Out” in data quality. Take a look at our DQ360 product which will help you with your data quality issues.
| What's In | What's Out |
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Transparency Financial Stability Market Surveillance Operational Ontologies Capability Measurement Governance Implementation Total Cost of Ownership Links and Relationships Regulatory Rule-Making Legal Entity Identifier Attribute-Based Classification Interconnected Big Data Granular Reporting Open Source Identifiers Semantic Definition Meaning Natural Language Data Visualization Legal Facts Flexible Architecture Data Manufacturing Data Comparability Information as an Asset Strategic Data Management Added Value Data Quality Rules Data Management Maturity Data Harmonization Utilities Regulatory Collaboration Incremental migration Data Alignment Requirements management Business Alignment Front-to-Back Linkages Exception Management System of Record Client Benefits Risk and Compliance Business Case Office of Financial Research |
Disclosure
Systemic Risk Market Abuse Data Models Performance Metrics Governance Structure Return on Investment Structure Legislative Objectives Global Location Number Hard Coded Classification Aligned Data Overload Aggregated Reporting Proprietary Identifiers Schema Definition Labels Message Syntax Data Analytics Data Structures Legacy Systems Data Remediation Data Mapping Data Importance Tactical Data Management Competitive Advantage Duplicate Sourcing Operational Risk Management Data Workflow Shared Services Regulatory Mandate Rip and Replace Cross Referencing Data Measurement Requirements Capture Top Down Management Data Cleansing Transformed Truth Find and Fix Golden Copy Value to Business Logical Business Case Systemic Opacity |
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