Data Steward
Support data governance processes
What You Do Today
You participate in data governance councils, present issues and recommendations, and ensure governance decisions are implemented across the organization.
AI That Applies
AI generates governance meeting materials from data quality metrics, policy compliance data, and open issue summaries.
Technologies
How It Works
The system ingests data quality metrics as its primary data source. The automation engine executes each step in the process sequence — validating inputs, applying business rules, generating outputs, and routing exceptions to human review queues. The output — governance meeting materials from data quality metrics — surfaces in the existing workflow where the practitioner can review and act on it.
What Changes
Governance meeting preparation becomes automated, with AI compiling the data and metrics that inform decisions.
What Stays
Presenting the issues, advocating for data quality investment, and the organizational influence that makes governance decisions stick.
What To Do Next
This section won't tell you what your numbers should be. It will show you how to find them yourself. Every instruction below produces a real, verifiable result in your organization. No benchmarks, no projections — just the steps to build your own evidence.
Establish Your Baseline
Know where you are before you move
Before adopting AI tools for support data governance processes, understand your current state.
Without a baseline, you can't measure whether AI actually improved anything. You'll adopt tools without knowing if they're working.
Define Your Measures
What to track and how to calculate it
Time per cycle
How to calculate
Measure how long support data governance processes takes end-to-end today, then after AI adoption.
Why it matters
The most visible improvement is speed. If AI doesn't save time, question whether it's adding value.
Quality of output
How to calculate
Track error rates, rework frequency, or stakeholder satisfaction scores before and after.
Why it matters
Speed without quality is just faster mistakes. Measure both.
Start These Conversations
Who to talk to and what to ask
your VP Data or Chief Data Officer
“Which steps in this process are fully rule-based with no judgment required?”
They set the data strategy that your pipelines serve
your data governance lead
“What's the error rate on the manual version, and what would "good enough" look like from an automated version?”
AI-generated data transformations need governance oversight
Check Your Prerequisites
Confirm readiness before you invest
Check items as you confirm them.