# Data Quality Insights and Guidance from Qualytics ## Data Quality vs Data Control: Why AI Demands Controls AI removes the human safety net that contained bad data. The data control layer validates data at the moment it's acted on. **Gorkem Sevinc** CEO & Co-Founder May 19, 2026 7 min read ## The Data Quality Maturity Model: Moving from Incident Response to Proactive Data Trust A framework outlining how organizations evolve data quality from reactive detection to proactive, governed control across increasingly complex data environments. [Click to View All resources from this category](https://qualytics.ai/resources/blog) ## Free Tools ### Data Quality Maturity Assessment Score your data quality program across seven dimensions. See your maturity level, where gaps exist, and whether you're ready for AI. .png) ### Cost of Bad Data Calculator Take 2 minutes to estimate what poor data quality is costing your organization, based on your industry, team, and current approach. ## Reports ### Data Quality vs. Data Observability This guide demystifies the Data Observability and Data Quality disciplines so you can determine which approach will set your organization up for lasting success. ## Guides ### Data Quality Automation: How Modern Platforms Validate at Scale Learn how automated data quality platforms infer validation rules, detect anomalies, and support remediation at scale. ### From Reactive to Reliable: A Guide to Modern Data Quality Frameworks Learn the six core components of a data quality framework and how they work together to ensure reliable data. ### What to Look for in Data Quality Software: A Guide to Features Learn which data quality software features help teams build and sustain scalable, automated quality programs. ## Customer Stories ### Catching Financial Data Issues Before They Impact Quarterly Close: A Global Alternative Asset Management Firm + Qualytics Automated reconciliation at scale, reducing manual effort and accelerating financial data confidence. .png) ### Powering Proprietary Credit Data at Scale: Octus + Qualytics Scaled trusted data operations while reducing QA costs and empowering domain experts. ### Catching Hidden Data Quality Errors Before They Cost Millions: MAPFRE USA + Qualytics Shifted from reactive cleanup to proactive controls, preventing costly downstream data errors. ## The Latest Product News ### How to Validate Semi-Structured Data (Arrays, Structs, and Nested JSON) Without Flattening Qualytics introduces native validation for nested JSON, arrays, and structs, enabling comprehensive data quality checks without costly flattening pipelines. ### Trusted AI and Analytics at Scale with Databricks and Qualytics AI-augmented data quality on Databricks, delivering proactive profiling, scalable rules, continuous monitoring, and governed remediation for trusted analytics and AI. .png) ### What We Delivered in 2025 to Empower Data Quality Teams in 2026 A look at the ten Qualytics features shipped in 2025, built to help data quality teams operate at scale and support AI, governance, and analytics.