AI and ML projects need high-quality data. Who is responsible for ensuring that data is accurate, complete, and reliable? Our view working with leading Fortune 500 customers is simple: Data quality is a team sport.

Here are our best practices for fostering a data culture:

1. Define a clear data strategy
2. Make data quality a shared responsibility
3. Empower business teams to own their data
4. Align incentives and budgets
5. Cultivate a culture of trust and collaboration

Organizations that successfully scale data quality don’t just enforce rules. They create a culture of shared responsibility where business and data teams proactively work together.