The foundation: Why Temporal for a data pipeline?

Houman Kargaran, Engineering Lead at ANZ Bank, discusses building a PII-compliant complaint ingestion pipeline using Temporal as the orchestration layer, ensuring that sensitive data does not leave the enterprise's infrastructure. The pipeline processes CSV files containing customer complaints by detecting PII, classifying them with an internal ML model, redacting sensitive information, and enabling semantic search. Key requirements include maintaining data within the enterprise, ensuring no complaints are lost, and making the system resilient, consistent, and observable. Temporal is chosen for its ability to provide durable execution, retries, and a detailed audit trail, aligning with compliance needs. The article outlines how Temporal's capabilities address both functional and non-functional requirements, including resilience, consistency, availability, and observability, and describes how each step in the pipeline is managed as a discrete Temporal Activity with specific retry policies. The series will continue to explore each layer of the system in detail, explaining the integration of Temporal with Pub/Sub, security boundaries, and activity chaining.

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