What does your Data Governance Checklist look like?

Most organisations overestimate what they need to "start" data governance. You don't need a giant framework, a dozen committees, or a library of policies. Honestly, you don't need much at all. What you do need is a few intentional habits - and those habits will naturally evolve as your data maturity grows. 

We've pulled together three simple checklists tailored for each different stage of the data governance maturity journey. Pick the one that feels closest to where you are today and use it as a practical starting point. 

If you’re just getting started (Foundational Maturity) 

This is for you if you're still figuring out what data you have, who's actually using it, and where the messiest risks are hiding. 

• Identify your most critical datasets or reports 
  
  
• Assign clear ownership and accountability 
  
  
• Document basic definitions and business terms 
  
  
• Establish simple access rules based on need and purpose 
  
  
• Start a lightweight log of data issues and impacts 
  
  
• Create a central place to store definitions and decisions 

This is your "Minimum Viable Governance" - small, simple, and immediately valuable. 

If you’re growing usage and complexity (Intermediate Maturity) 

Try this on for size if you have more users, more data products, more decisions - and more chances for chaos. 

• Define a standard approach for certifying or endorsing trusted data 
  
  
• Introduce naming conventions for datasets, metrics, and reports 
  
  
• Track lineage for key data flows and decision‑critical outputs 
  
  
• Establish quality rules and monitoring for important data 
  
  
• Create a governance working group or decision forum 
  
  
• Embed trust signals (ownership, definitions, quality status) where people consume data 

This is where governance becomes visible and starts reducing rework, duplication, and confusion. 

If you’re preparing for AI or advanced analytics (Advanced Maturity) 

If you're thinking big - risk, assurance, and scaling responsibly (without losing your mind), then this is for you: 

• Define service levels for data products (freshness, quality, availability) 
  
  
• Monitor usage, cost, and performance of data assets 
  
  
• Establish documentation standards for models and analytical products 
  
  
• Create approval pathways for new or high‑risk use cases 
  
  
• Strengthen metadata management and classification 
  
  
• Automate policy enforcement where possible 
  
  
• Build training and enablement for responsible data use 

This is where governance shifts from "control" to "confidence". It's also where you enable innovation, whilst balancing safety and accountability. 

Need clarity? Try this tip

No matter your organisation's maturity level. Each checklist starts with identifying or defining "something". It might be helpful for you to start with everything on one page. Start a register of business decisions that are informed by data (include the decisions that should be informed by data, but aren't - yet). Find and document which data sources are being used for these decisions - this is how you define the tangible business value from each data asset. This process will help you find clarity when identifying or defining according to your checklist. 

Where to next? 

No matter your maturity, governance grows best through small, consistent steps. Start where you are, build what you need, and let your governance evolve as your organisation does. 

If you're not sure which maturity stage you're in or what to tackle first, Altis can help you identify quick wins, clarify ownership, and build a governance foundation that actually sticks. Book a governance readiness session with Altis today and take control of your data with confidence.