dataimportexport

Data import and export, commonly referred to as data import/export, describes the processes by which data is moved between information systems. Import brings external data into a target system; export extracts data from a source for use elsewhere. These capabilities are central to data integration, system migration, backups, and interoperability across applications, databases, and cloud services.

Formats and methods vary. File-based exchanges use CSV, JSON, XML, Parquet, Avro, and Excel, often with schemas or contracts. Programmatic approaches rely on APIs (such as REST or GraphQL), SQL dumps, or messaging protocols. Data can be transferred through middleware, enterprise integration tools, ETL/ELT platforms, or custom scripts. Successful data exchanges usually involve explicit mapping and transformation to align source and target schemas.

Workflows include extraction, transformation, and loading, with validation and error handling. Incremental or delta exports, change data capture, and scheduled batch processing are common patterns. Metadata about origins, transformations, and lineage supports data governance and audit trails. Security practices include encryption in transit and at rest, access controls, and provenance logging.

Challenges include ensuring data quality and schema compatibility, handling data type differences, performance constraints, and retry logic. Schema evolution, versioning, and backward compatibility require coordination between systems. Compliance and privacy considerations—such as PII protection and regulatory constraints—must guide data handling.

Typical applications span data warehousing and analytics, cloud migrations, CRM/ERP integration, content management, data sharing between organizations, and disaster recovery backups.