Data Governance Framework

Governance = Trusted Enterprise Data

Governed Data provides an organization with clean and trusted data, enabling it to ultimately drive towards better customer value, experience, and loyalty. Data Governance also allows organizations to reduce its cost in complying with various regulatory policies as they are established across markets and industries.

Data Governance has been defined by DAMA as follows:

“Data Governance is the exercise of authority and control over the
management of data assets.”

Next Pathway’s Data Governance Framework helps organizations accelerate the implementation of a Data Governance practice, by addressing key governance building blocks, including organizational structure and roles, processes, policies, standards and best practices.

In order to be most effective, Data Governance must be aligned with the overall business strategy. This is achieved by setting a number of goals, which will help to achieve the business targets specified in the strategy.

Next Pathway’s approach to designing, implementing and governing a Data Governance Framework is comprised of the following 4 phases:

  • Phase 1: Define the Data Governance Framework.
  • Phase 2: Establish the Data Governance Organizational Structure.
  • Phase 3: Conduct a pilot to test the Framework, and Structure.
  • Phase 4: Operationalize the Framework by integrating the processes and structure within existing projects and monitor for continuous improvement.

Note: Next Pathway’s Data Governance Framework adheres to the following industry standards:

  • DAMA DMBOK for guidance on data governance, and decision making, and escalation related to data issues.
  • CMMI for the development of the data governance maturity model.
  • ISO 20022, ACORD, FIBO for recommendations on Business Term Glossary.
  • BCBS 239 to ensure the framework supports the governance requirements specified in Basel 239.
  • EDM DCAM for the development of data quality templates.

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