Data Orchestration Explained – and Why You Shouldn't DIY

Data orchestration is crucial for managing modern data pipelines, ensuring reliability and efficiency. Traditional ETL processes required custom-built transformations by engineering teams, while DIY scheduling methods did not scale well. Modern orchestration tools leverage programming languages like Python to design complex, robust, and dynamic systems. These tools follow the workflows-as-code paradigm and include products such as Luigi, Apache Airflow, Dagster, Prefect, AWS Step, Google Cloud Composer, Argo, and Tekton. The modern data stack consists of specialized tools that handle orchestration internally, reducing the need for separate orchestration tools in many cases. However, specific use cases may still require in-house orchestration systems, such as ETL processes with unique requirements or custom scripts for data products. Overall, data orchestration is a vital component of modern data management, but its role varies depending on the business's needs and the capabilities of their chosen tools.