Alation

Automatically scans and discovers data assets across multiple sources, databases, data warehouses, and cloud platforms without manual configuration. Uses machine learning to identify and catalog tables, columns, schemas, and data objects with minimal human intervention.

Automatically traces data flow and dependencies across systems, showing how data moves from source to destination through transformations and pipelines. Uses AI to infer lineage relationships even when explicit metadata is unavailable.

Allows stewards to enrich automatically discovered metadata with business context, descriptions, and relationships. Supports collaborative curation where multiple users can contribute to improving catalog quality.

Defines and enforces data governance policies across the organization, including access controls, data retention rules, and usage restrictions. Integrates with data systems to prevent policy violations.

Analyzes the potential impact of changes to data assets by identifying all downstream dependencies and affected systems. Helps teams understand consequences before making modifications.

Creates and maintains a centralized business glossary with standardized definitions of business terms and metrics. Enables linking of technical data assets to business concepts for better alignment.

Automatically generates business-friendly documentation for data assets by analyzing schemas, sample data, and usage patterns. Creates descriptions, definitions, and context without requiring manual documentation effort.

Provides a natural language chat interface where users can ask questions about data assets, lineage, and relationships using plain English. Returns relevant datasets, documentation, and context without requiring technical query knowledge.

Manages data governance tasks through automated workflows including steward assignments, data quality issue escalation, and approval processes. Routes governance tasks to appropriate owners and tracks completion.

Continuously monitors data quality metrics across cataloged assets and alerts stewards when quality issues are detected. Tracks metrics like completeness, accuracy, and freshness with configurable thresholds.

Tracks data assets against compliance requirements and regulations (GDPR, CCPA, HIPAA, etc.), identifying sensitive data and ensuring governance controls are in place. Generates compliance reports and audit trails.

Enables systematic tagging and classification of data assets using custom taxonomies and business terms. Supports both automated classification based on content analysis and manual tagging by stewards.

Connects to and catalogs data from diverse platforms including relational databases, data warehouses, cloud storage, BI tools, and data lakes. Provides unified view across heterogeneous data environments.

Tracks how data assets are used across the organization, showing query patterns, user access, and popularity metrics. Provides insights into data utilization and identifies unused or underutilized assets.