Data Ingestion

ˈdeɪtə ɪnˈdʒɛsʧən

Data ingestion is the process of obtaining and importing data for immediate use or storage in a database. It involves collecting data from various sources, such as databases, APIs, or files, and then transforming it into a format suitable for analysis or processing. Common characteristics of data ingestion include batch processing, where data is collected over time, and real-time ingestion, where data is collected and processed instantly. This process is crucial in data pipelines, enabling organizations to leverage big data analytics, machine learning, and other data-driven applications. Use cases include feeding data into machine learning models, updating data warehouses, and integrating data from different platforms for comprehensive analysis.