The Data Engineering Part 2: Building Your First Production Data Pipeline

1. 1Build a data pipeline using Kafka for data ingestion
2. 2Process data in real-time using Spark
3. 3Transform data using dbt for analytics
4. 4Schedule and manage workflows with Airflow
5. 5Configure data storage for querying and dashboarding

Data engineers and analysts can benefit from this tutorial to build scalable data pipelines, while data scientists can use the output for modeling and analysis

💡 A modern data pipeline architecture should include real-time data processing, scalable data storage, and automated workflow management

📊 Build your first production data pipeline with Kafka, Spark, dbt, and Airflow! 💻