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FIELD REPORT · DATA

Data Pipeline Architecture: ETL/ELT Best Practices

Build robust data pipelines. Apache Airflow, dbt, and cloud-native solutions.

PUBLISHED
September 18, 2025
UPDATED
May 15, 2026
READ TIME
1 MIN
AUTHOR
ONE FREQUENCY
KEY FACTS
Topic
data, etl, pipeline
Published
September 18, 2025
Last updated
May 15, 2026
Read time
1 min
Word count
73

Modern data pipelines power analytics and ML. Build robust, scalable solutions.

Architecture Patterns

  • Batch processing
  • Stream processing
  • Lambda architecture
  • Kappa architecture

Technology Stack

  • Orchestration: Airflow/Prefect
  • Processing: Spark/Beam
  • Transformation: dbt
  • Storage: Data lakes/warehouses

Best Practices

  • Idempotent operations
  • Data quality checks
  • Schema evolution
  • Monitoring and alerting

Performance

  • Partitioning strategies
  • Incremental processing
  • Caching layers
  • Cost optimization
SOURCES

Cited and consulted.

  1. 01Martin Fowler — Data Mesh Principlesmartinfowler.com
  2. 02DAMA DMBOK — Data management body of knowledgedmbok.org
  3. 03Apache Airflow Documentationairflow.apache.org
  4. 04dbt Labs Documentationdbt-labs.com
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