Technical
Auto-Discovery Architecture
How DataInc.ai automatically maps your marketing data ecosystem using intelligent scanning and inference.
Page Metadata
- Meta Title
- Auto-Discovery Architecture | DataInc.ai Technical Docs
- Meta Description
- Learn how DataInc.ai's Auto-Discovery scans, classifies, and maps marketing data assets in your warehouse.
- Primary Keywords
- auto-discovery architecturedata cataloging
- Secondary Keywords
- schema scanningmetadata inferencedata mapping
Architecture Overview
Scanning engine
Classification system
Relationship inference
Auto-Discovery uses a multi-stage pipeline: warehouse connection, schema scanning, marketing-aware classification, and relationship inference.
Warehouse Connectivity
Supported platforms
Connection methods
Security model
Secure connections to Snowflake, BigQuery, Redshift, and Databricks with minimal permissions required.
Schema Scanning
Table discovery
Column profiling
Sample analysis
Efficient scanning techniques to profile large schemas without impacting warehouse performance.
Marketing Classification
Channel detection
Campaign patterns
Conversion tables
ML-powered classification that recognizes marketing data patterns specific to channels, campaigns, and conversions.
Relationship Inference
Key detection
Join path discovery
Lineage mapping
Automatically infer relationships between tables based on key patterns and data overlap.
Continuous Monitoring
Once discovered, assets are continuously monitored for changes with efficient delta detection.