19、DataOps: Streamlining Data Pipeline Development and Deployment

DataOps: Streamlining Data Pipeline Development and Deployment

1. Data Pipeline Environments

Organizations are constantly in need of creating new or enhancing existing data products, all of which rely on data pipelines. Modern data pipelines have expanded beyond traditional ETL for data warehouses and now include machine - learning models and data visualization. However, traditional methods of creating and modifying pipelines are too slow to meet the demand for hundreds or thousands of new pipelines.

The creation and update of data pipelines from source to product should be as fast and automated as possible. Similar to software development, DataOps development occurs in clones of the production data pipeline, using the same tools and languages to facilitat