2025-02-12 Overview of data governance

Brain Parish, IData, CEO and Founder

Governing what? (Content)

• Data definitions

• Data deliverables catalog - reports, ETL, surveys, APIs, etc.

• Data requests - tracking requests and how you’re responding to it, how long it takes, making sure deliverable matches needs

• Data inventory and lineage - understanding all the different data systems in your organization - data lakes, marts, shadow systems; how data moves between those systems - where it comes from/goes; technical metadata for these systems

• Data quality - quality rules (technical/referential, complex business logic, how many records do we have that we violate the rules, assessment. Issue resolution - managing data quality issues: root cause analysis, data cleanup.

• Data policies - understanding data sharing, data persistence, overall governance/charter, policy documents

• Data access, security, and privacy - control who has access and how to get it, what can you do with the data, who you share it with

What is governance? (Stewardship, processes, completeness, adoption)

• Stewardship - committee assigning responsible parties

• Standard, controlled and understood processes - how do you make data definitions, how do you document, how do people access it, how do people request data definitions

• Agreed-upon and complete information - more broad, creates usage

• Adoption, buy-in, and use of information

Framework for data governance (best practice)

• Define and establish stewardship structure (key stakeholders)

• Establish data governance knowledge base: Tool to facilitate and stores the information.

  • Open to all consumers/creators

• Establish a communication process

  • Support data request process

  • Supports data steward activity (approval, rejection, advice)

  • Facilitate just-in-time data governance

    • Interact with the governance KB/stewards at that moment to get the answers they need

Content best practices

Open

Taking a pragmatic approach

• DG is about best practices designed to help people access, understand, connect, and effectively use your organization’s data across all systems.

Thinking of data governance like academic advising

• Seek out a person who understands requirements (stewardship)

• Catalog has all the rules and requirements (content)

• Knowing who to talk to, who is my advisor (processes)

• Looking at the known information, and there’s substantial useful content that’s updated regularly (completeness)

• Adoption, promotion/training, outreach, how everyone interacts with the governance process

Who participates in data governance?

• Data consumers and requesters

• Analysts and report creators

• Data stewards

  • functional - understands their area but not technical

  • technical - augment with technical details

• Data managers and leadership

• Data system technical resources

Scope of data governance

• DG should be shared and standardized across your entire organization.

• Decide the scope to start. Starts with one area and use it as a model to bring to the organization