Types of data governance frameworks

Data Governance Concepts

Courtney Smith

Strategic Initiatives Manager

Choosing a type of framework

Three types of frameworks:

  1. Traditional top-down
  2. Traditional bottom-up
  3. Collaborative approach

Framework should align with:

  • Priorities and desired outcomes
  • Regulatory requirements
  • Organization size

Image to depict a business framework

Data Governance Concepts

Traditional top-down approach

Characteristics:

  • Small team of data providers
  • "Gatekeepers" control data use and access
  • Well-defined best practices
  • Centralized protection, governance, control

Challenges:

  • Not easily scalable with small team
  • Difficult to manage increased data volume and demand

Pyramd with an image pointing from top to bottom

Data Governance Concepts

Traditional bottom-up approach

Characteristics:

  • Prioritizes data democratization
  • More scalable than the top-down approach
  • Controls implemented after raw data is ingested

Challenges:

  • Hard to ensure consumers use governed, not raw, data
  • Potential increase in regulatory risk and data management costs

Pyramid icon with arrow pointing from bottom to top

Data Governance Concepts

Collaborative approach

Characteristics:

  • Flexible and scalable
  • Balances defensive and offensive strategy
  • Relies on stakeholder collaboration
  • Goal: trusted, accessible enterprise data

Challenges:

  • Must follow well-defined data principles
  • May not fulfill all regulatory needs

Stack of hands to show unity and teamwork

Data Governance Concepts

DAMA Data Management Body of Knowledge

Comprehensive guide on:

  • Standard data management functions
  • Standard terminology
  • Industry best practices
  • Data governance as a unifying theme

Image of the DAMA Data Management Body of Knowledge wheel that displays the ten different data management knowledge areas.

1 DAMA. Earley, S., & Henderson, D., Sebastian-Coleman, L (Eds.). The DAMA Guide to the Data Management Body of Knowledge (DAMA-DM BOK). Bradley Beach, NJ: Technics Publications, LLC. 2017.
Data Governance Concepts

DGI data governance framework

Ten components under three core areas:

  • People and organizational bodies
  • Rules and rules of engagement
  • Processes

Guidance based on organizational focus:

  • Data quality
  • Data warehouses and business intelligence
  • Management support

Image of the DGI data governance framework that contains ten components grouped into three core areas.

1 The Data Governance Institute. Thomas, G. The DGI Data Governance Framework. 2020
Data Governance Concepts

EDM Council's DCAM Framework

  • Helpful for financial institutions with regulatory requirements
  • Industry-leading resource on:
    • Implementing data management practices
    • Key capabilities
    • Organizational structure
    • Standard terminology
    • Progress monitoring
1 edmcouncil.org, 2022
Data Governance Concepts

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Data Governance Concepts

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