datamapping

Datamapping is the process of creating a formal correspondence between elements of a source data structure and elements of a destination data structure. It is a core activity in data integration, data migration, and data transformation projects, enabling systems with different schemas to exchange or merge data. A mapping specifies where each input field should be placed in the output, and may also define transformations, type conversions, value lookups, and enrichment rules.

Key concepts include source and target schemas, mapping rules, and the handling of data types, nulls, and defaults. Mappings may be one-to-one, one-to-many, or many-to-one, and can involve complex logic such as concatenation, formatting, or calculations. Lookups, joins, and reference data are often used to resolve codes and to enrich data during the mapping process. Metadata about mappings supports traceability, auditing, and impact analysis.

Mappings can be defined manually by data engineers or generated by mapping tools that infer correspondences from schema metadata. They are commonly expressed in mapping languages or configurations, using techniques such as XSLT for XML, SQL-based transformations, or JSONata for JSON, as well as specialized ETL or data integration platforms.

Applications include extracting data from operational systems into data warehouses, integrating data across applications, and preparing data for APIs or analytics. Important considerations include data quality, data type coercion, error handling, performance, and maintainability, as well as governance and lineage to track data origin and transformation steps.