Data Quality & Profiling

Check for broken cross-references in collections. Returns objects with references to deleted or non-existent objects.

Analyze vector embeddings distribution. Shows dimensionality, magnitude statistics, density, and similarity patterns. Critical for understanding embed...

Find objects without vector embeddings. Critical for debugging semantic search issues - objects without vectors won't appear in similarity searches.

Validate objects against collection schema definition. Checks if objects have all required properties and correct data types.

Find near-duplicate objects using vector similarity. Helps identify redundant data and potential data quality issues from duplicate imports.

Generate comprehensive data quality report. Combines vector quality, property completeness, duplicates, and collection health into a single report wit...

Check vector quality for corruption issues. Detects zero vectors, NaN values, and vectors with abnormal magnitude. Critical for maintaining search qua...

Validate property completeness and quality. Find objects with null, missing, or empty required properties. Essential for data quality monitoring.

Generate comprehensive collection profile with statistics on object count, properties, vectors, and overall health. Essential starting point for under...

Analyze distribution of values for a specific property. Shows top values, uniqueness, null rate, and statistics. Essential for understanding data patt...