Enterprise Data Governance

Data governance (DG) refers to the overall management of the availability, usability, integrity, and security of the data employed in an enterprise. A sound data governance program includes a governing body or council, a defined set of procedures, and a plan to execute those procedures. The initial step in the implementation of a data governance program involves defining the owners or custodians of the data assets in the enterprise. A policy must be developed that specifies who is accountable for various portions or aspects of the data, including its accuracy, accessibility, consistency, completeness, and updating. Processes must be defined concerning how the data is to be stored, archived, backed up, and protected from mishaps, theft, or attack. A set of standards and procedures must be developed that defines how the data is to be used by authorized personnel. Finally, a set of controls and audit procedures must be put into place that ensures ongoing compliance with government regulations.

Data Governance Considerations:

  • Executive sponsorship
  • Establish a dedicated team of Global Data Managers, Application Stewards, Data Stewards, and Leadership review
  • Establish both proactive and reactive processes for Data Relationship Management.
  • Use a holistic approach: people, process, technology and information
  • Build your processes to be ongoing and repeatable, supporting continuous improvement
  • Stay current with vendor-provided patches
  • Budget for Data Governance improvements
  • Align Master Data Management with strategic business goals
  • Organizational Change Management

One of the most precious assets a company possesses is their data. More specifically, financial figures, statistics,hierarchies, chart of accounts, customers, products, segments, master data, metadata, attributes, properties, mappings, etc. AdvancedEPM offers a two week Enterprise Data Management Insight & Diagnostic Workshop that touches on each of these areas and begins to frame the conversation for future introspection & action so as to align your enterprise with true industry best practices.

Workshop deliverables include:

  • Detailed Diagnostic Assessment
  • Executive Summary Presentation (Current State vs. Industry and Like–‐Sized Organizations)

Topics of Discussion & Analysis Include:

  • Data Origination
  • Data Volume
  • Update Frequency
  • Bi Directionality
  • Data Dictionary / Business Glossary
  • Storage Capability and Preference(s)
  • Transformation / Data Manipulation
  • Data Formats, Sources and Targets
  • Data Mappings
  • Levels of Granularity
  • Data Gaps / Process Gaps
  • Exception Handling and Notification
  • Data Cleansing, Data Staging
  • Database Normalization
  • Data Deduplication
  • Change Data Capture
  • Data Matching
  • Backup & Recovery Processes & Procedures
  • Reference Architecture
  • Dependencies (Systematic)
  • Data Governance / Approvals / Workflow
  • Data lineage