Data Foundations · Module 10
Data roles and responsibilities
Roles exist so someone is accountable for quality, access, and change.
Previously
Data lifecycle and flow
Data starts at collection, gets stored, processed, shared, and eventually archived or deleted.
This module
Data roles and responsibilities
Roles exist so someone is accountable for quality, access, and change.
Next
Foundations of data ethics and trust
Ethics matters from the first data point.
Progress
Mark this module complete when you can explain it without rereading every paragraph.
Why this matters
Data owners make decisions about purpose and access.
What you will be able to do
- 1 Explain data roles and responsibilities in your own words and apply it to a realistic scenario.
- 2 Data work improves when decision rights and responsibilities are explicit.
- 3 Check the assumption "Decision rights are explicit" and explain what changes if it is false.
- 4 Check the assumption "Consumers can report issues" and explain what changes if it is false.
Before you begin
- No previous technical background required
- Read the section explanation before using tools
Common ways people get this wrong
- Everyone responsible means no one responsible. When responsibility is shared, fixes are delayed. Make ownership clear.
- Unowned breaking changes. If producers change fields without notice, downstream systems fail quietly.
Roles exist so someone is accountable for quality, access, and change. Data owners make decisions about purpose and access. Data stewards guard definitions, metadata, and policy. Data engineers build and maintain pipelines. Data analysts turn data into insights. Data consumers use the outputs responsibly. When roles blur, pipelines stall, privacy is ignored, or dashboards contradict each other.
Mental model
Ownership prevents chaos
Data work improves when decision rights and responsibilities are explicit.
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1
Owner
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2
Steward
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3
Producer
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4
Consumer
Assumptions to keep in mind
- Decision rights are explicit. Someone decides when a definition changes and when a dataset is fit for purpose.
- Consumers can report issues. If users cannot report problems, you only learn when outcomes fail.
Failure modes to notice
- Everyone responsible means no one responsible. When responsibility is shared, fixes are delayed. Make ownership clear.
- Unowned breaking changes. If producers change fields without notice, downstream systems fail quietly.
Check yourself
Quick check. Roles and responsibilities
0 of 7 opened
What does a data owner decide
Purpose and access.
What does a data steward maintain
Definitions, metadata, and policy alignment.
What does a data engineer build
Pipelines and storage that move and prepare data.
What does a data analyst do
Turns data into insights and stories.
Who is a data consumer
Anyone using the outputs responsibly.
Scenario. A dashboard number looks wrong. What is a sensible first move before arguing
Ask for the definition and lineage. Then involve the owner or steward for meaning, and the engineer for pipeline evidence.
What happens when roles blur
Confusion, stalled work, or risky decisions.
Artefact and reflection
Artefact
A short module note with one key definition and one practical example
Reflection
Where in your work would explain data roles and responsibilities in your own words and apply it to a realistic scenario. change a decision, and what evidence would make you trust that change?
Optional practice
Pair scenarios with the role responsible for the next action.