Data Ingestion Pipeline

Overview#

The Data Ingestion Pipeline provides a robust, scalable system for importing, normalizing, and processing data from diverse external sources. The pipeline handles schema mapping, entity extraction, data validation, correlation with existing records, and integration with the platform's data model -- supporting batch imports, real-time streaming, and scheduled synchronization with configurable error handling and retry logic.

Key Features#

• Multi-Source Ingestion -- Import data from file uploads (CSV, JSON, XML), API integrations, database connections, streaming sources, and scheduled pull jobs
• Visual Schema Mapping -- Map source fields to destination schemas with a visual interface supporting type conversion, validation rules, default values, and conditional logic
• Entity Extraction -- Automatically extract named entities, detect relationships, link to existing records, and assign confidence scores during ingestion
• Deduplication -- Identify and handle duplicate records during import to prevent redundant data from entering the system
• Dead Letter Queue -- Capture failed records in a review queue for investigation and reprocessing without blocking the overall pipeline
• Incremental Updates -- Support incremental synchronization with external databases to efficiently process only changed records on a configurable schedule
• Conflict Management -- Detect and resolve conflicts when ingested data contradicts existing records, with configurable resolution strategies
• Progress Tracking -- Monitor import job status in real-time with detailed metrics on processed, successful, and failed records
• Validation and Error Reporting -- Validate every record against schema rules and business logic, with categorized error reporting for missing fields, type mismatches, format errors, and constraint violations
• Rollback Capability -- Reverse completed import jobs if issues are discovered after processing, restoring the system to its pre-import state

Use Cases#

• Records Management Integration -- Import records management data by mapping source fields to platform schemas, extracting entities from narrative text, validating required fields, and correlating with existing records automatically.
• External Database Synchronization -- Configure ongoing synchronization with external databases using scheduled incremental updates, conflict resolution, and health monitoring to keep data current.
• Historical Data Migration -- Migrate large volumes of historical data with progress tracking, error recovery, validation reporting, and rollback capability to safely onboard legacy datasets.
• Multi-Source Data Consolidation -- Combine data from multiple file formats and API sources into a unified data model with entity linking and deduplication across sources.
• Streaming Data Ingestion -- Process real-time data streams with continuous validation, entity extraction, and automatic correlation to support time-sensitive operational workflows.

Integration#

The Data Ingestion Pipeline connects with the platform's entity resolution, data quality monitoring, schema management, and integration hub modules to provide end-to-end data onboarding from source systems through validation and enrichment to the unified data model.

Last Reviewed: 2026-02-05