Data engineering forms the backbone of every data-driven organization. Without reliable pipelines, even the best machine learning models are useless.
Modern data pipelines rely on tools like Apache Spark, dbt, and Airflow. The trend is moving away from classic ETL processes toward ELT, where raw data is loaded first and then transformed.
Streaming architectures with Kafka or Pulsar complement batch processing where real-time data is needed. Choosing the right approach depends on the specific use case.
