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Trusted AI and Analytics at Scale with Databricks and Qualytics

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Dan Everett
Dir. Product Marketing
Mar 3, 2026
6 min read

What We Delivered in 2025 to Empower Data Quality Teams in 2026

Dan Everett
Dir. Product Marketing
Jan 14, 2026
5 min read

How to Detect Table and Schema Changes in Snowflake Using Time Travel

Gustavo Cardoso
Dec 17, 2025
3 min read

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.

AI-augmented data quality on Databricks, delivering proactive profiling, scalable rules, continuous monitoring, and governed remediation for trusted analytics and AI.

New in Qualytics: Agent Q, Complex Data Types, & Workflow Automation

February's releases expand data quality coverage to nested data types, add AI-assisted stewardship with Agent Q, and automate anomaly remediation workflows.

Faster Handoffs, Less Friction: What We Shipped in January 2026

What shipped in Qualytics this January: automated anomaly workflows, new ticketing integrations, and a cleaner, faster interface.

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.

This use case demonstrates how a Qualytics customer developed a lightweight monitoring process utilizing Snowflake Time Travel and Qualytics Quality Checks to surface data and schema changes within minutes, without requiring the addition of new pipelines or infrastructure.