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Concept for orchestrated execution of data and business transformations in pipelines focusing on reliability and reproducibility.
Transformation Execution describes orchestrated execution of data and business transformations within pipelines or processes. It covers scheduling, state management, parallelism and error handling to produce consistent, reproducible results. Applicable to ETL/ELT, streaming and batch scenarios in distributed environments and emphasizes observability and idempotent processing.
Measure of processed data units per unit time.
Time from ingest to availability of the result.
Share of failed transformations and retry attempts.
Combination of batch and streaming jobs to provide consistent reporting views.
Streaming transformations that enrich events with profiles and ensure low latency.
Phased migration runs with validation, compensation and fallback strategies.
Define requirements, SLAs and data quality rules
Modularize transformation logic and make it idempotent
Choose orchestrator, set up monitoring and checkpointing