Getting to Data Quality: Data Reliability in the AI era

Data reliability is critical in the AI era—your AI is only as reliable as the data behind it. The Collibra eBook outlines how fragmented governance is a major obstacle, and how unified governance ensures trust, compliance, and innovation. It introduces the concept of Data Confidence™, where organizations can safely scale AI initiatives with trusted data. The guide emphasizes a six-step framework to achieve data reliability:

• Profile the data: Discover and classify sensitive data sources.
• Define policies: Create rules and enforce compliance.
• Detect anomalies: Use ML to monitor data for irregularities.
• Monitor impact: Assess the business impact of data issues.
• Notify experts: Alert stakeholders for timely remediation.
• Optimize continuously: Improve governance through ongoing feedback.

Collibra’s solutions empower organizations with visibility, automation, and control—ensuring high-quality, compliant, and actionable data.