Data Management Maturity Assessment

A collaborative approach to the quantification of the maturity and process improvement for an organization’s data management capabilities.
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The Data Management Maturity Model (DMM) is intended as a comprehensive reference model for state-of-the-practice data management process improvement. The DMM defines the fundamental business processes of data management and specific capabilities that constitute a gradated path to maturity. It allows organizations to evaluate themselves against documented best practices, determine gaps, and improve management of data assets across functional, line of business, and geographic boundaries.

Through this assessment, Sandhill Consultants helps an organization understand what capabilities they will need to achieve a comprehensive enterprise scale data architecture.

Helping an organization to determine its competency to achieve higher levels of performance of it data management processes by driving an improvement strategy and delivering trusted reliable data.

Data Management Maturity Model

Capabilities and Process areas covered by the DMM Assessment are:

  • Data Management Strategy – Strategy, Communications, Data Management
    Function, Business Case and Funding
  • Data Governance – Governance Management, Business Glossary and Metadata
    Management
  • Data Quality – Quality Strategy, Data Profiling, Data Assessment and Cleansing
  • Data Operations – Data Requirements Definition, Lifecycle Management and Provider
    Management
  • Platform and Architecture – Architectural Approach and Standards, Data
    Management Platform, Data Integration, Historical Data, Archiving and Retention.
  • Supporting Processes – Measurement and Analysis, Process and Risk Management,
    Configuration Management and Process Quality Assurance.

 

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Key Benefits:

  • Shared vision and understanding of data assets
  • Identification of strengths to be leveraged and gaps to be fixed
  • Risk mitigation, improved auditing and cost control
  • Strengthened data governance (collaboration and compliance)
  • Clear path for improvement in 25 process areas
  • Defined roles for stakeholders within each discipline
  • Competitive advantage resulting from improved data quality, trust in data, and ability to make sound strategic decisions
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