Data Ingestion
Data ingestion is the process of importing, transferring, and loading data from various sources into a storage system or processing environment for analysis or operational use. It involves collecting data from databases, APIs, files, streams, or external systems and making it available in a target system like a data warehouse, data lake, or application. This process often includes steps such as extraction, validation, transformation, and loading to ensure data quality and usability.
Developers should learn data ingestion to handle the increasing volume and variety of data in modern applications, enabling real-time analytics, machine learning, and business intelligence. It is essential in scenarios like building data pipelines for ETL (Extract, Transform, Load) processes, integrating data from IoT devices, or aggregating logs and metrics for monitoring systems. Mastery of data ingestion helps ensure efficient, scalable, and reliable data flow in data-driven projects.