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Bulk ETL Enforcement Point

The Bulk ETL Enforcement Point is optimised for processing high-volume, batch, and streaming datasets. It allows organisations to apply consistent eXate data protection policies, masking rules, and anonymisation workflows to massive files or databases during Extract, Transform, Load (ETL) operations.

Key Capabilities

  • High-Throughput Processing: Designed to handle gigabytes of data with minimal overhead, supporting parallel execution and distributed streams.
  • File and Schema Support: Seamlessly processes CSV, parquet, JSON, and flat file formats, as well as database-to-database replication pipelines.
  • Reversible Tokenisation: Supports bulk tokenisation/de-tokenisation, allowing massive datasets to be safely transferred to lower-environment testing zones.
  • Consistent Protection: Guarantees that batch-processed files share the exact same masking rules and cryptographic keys as those applied in real-time APIs or JDBC connections.

Common Use Cases

1. Secure Data Lake Ingestion

Anonymise or pseudonymise sensitive database fields before writing them into a public cloud data lake or data warehouse (e.g., Snowflake, BigQuery).

2. Test Data Generation / Sanitisation

Take a snapshot of production database tables, run them through a Bulk ETL sanitisation job, and load the safe, masked tables into pre-production test environments.

3. Cross-Border Data Transfers

Scan and mask datasets to ensure compliance with strict residency laws before exporting data across national or jurisdictional boundaries.

Configuration & Walkthrough Guides

For portal-based walkthroughs on building, running, and optimising Bulk ETL workflows (GatorSet), see the following guides: