What is data culture? A guide for data-driven organisations
Summary
Data culture is the set of shared values, practices and expectations that determine how an organisation accesses, understands and uses data to make decisions. It depends on widespread data literacy, trusted and interpretable data, governance and role-appropriate access so employees can base choices on evidence rather than hierarchy.
The article explains core tenets — data democratisation, data-driven decision-making, governance, literacy and trust — and contrasts data culture (a day-to-day mindset) with data strategy (a formal long-term plan). It then outlines common barriers (adoption, literacy, quality and security), benefits (efficiency, better decisions, risk management) and a 10-step approach CDOs can follow to build a strong enterprise data culture.
Key Points
- Data culture = shared principles that make data accessible, trusted and usable across the organisation.
- Core tenets: democratisation, evidence-based decisions, governance, literacy and data trust.
- Data culture is behavioural; data strategy is the formal plan that supports it.
- Common barriers include resistance to change, poor data skills, data quality issues and security trade-offs.
- Benefits include faster, evidence-based decisions, improved efficiency, empowered employees and better risk management.
- Ten recommended steps for CDOs: align analytics to business strategy, foster collaboration, use analytics for innovation, build a use-case roadmap, cultivate talent, form an advisory council, establish data management, use proven tech, partner externally and measure KPIs.
- Successful change requires senior business co-leadership, clear KPIs, and ongoing education and governance.
Why should I read this?
Short version: if you want your organisation to actually use data — not just collect it — this is the practical playbook. It’s a no-nonsense list of what stops teams from becoming data-driven and ten clear steps CDOs and leaders can take now to fix it. Read it if you’re trying to get buy-in, hire the right people, or prove the value of data projects.
Context and relevance
This guide matters as organisations scale analytics, adopt AI and face stricter regulatory and ethical demands. Building a reliable data culture reduces risk from poor-quality or siloed data, speeds up decision cycles and helps extract commercial value from analytics and AI investments. For leaders, the article connects cultural change to concrete governance, talent and technology actions — aligning with current trends in data democratisation and responsible AI.