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The data and ML tool map: hello worlds for dbt, Airflow, Spark, MLflow and friends, and when to use each
If you are new to data engineering or machine learning, the modern tool landscape can feel unnecessarily complicated.
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ELT and dbt: transforming data where it lives, with tests and lineage
ELT changes the center of gravity of a data pipeline.
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Tools: dbt, Redshift Spectrum, Athena
This article explores how dbt, Redshift Spectrum, and Amazon Athena form a modern, cloud-native data engineering stack. It explains their roles, integration patterns, performance tuning strategies, and best practices for scalable analytics in 2025. The focus is on combining transformation, metadata, and serverless querying for efficient lakehouse workflows.