concept

Data Mapping

Data mapping is the process of defining relationships between data elements in different data models, schemas, or formats to enable data transformation, integration, or migration. It involves creating a set of rules or mappings that specify how data from a source (e.g., a database, API, or file) is converted, transformed, or linked to a target destination. This is fundamental in ETL (Extract, Transform, Load) processes, data warehousing, system integrations, and data migration projects.

Also known as: Data Transformation Mapping, Schema Mapping, ETL Mapping, Data Integration Mapping, Field Mapping
🧊Why learn Data Mapping?

Developers should learn data mapping when working on projects that involve integrating disparate systems, migrating data between databases or applications, or building data pipelines for analytics and reporting. It is essential in scenarios like merging data from multiple sources (e.g., CRM and ERP systems), ensuring data consistency during software upgrades, or preparing data for business intelligence tools. Mastery of data mapping helps prevent data loss, maintain integrity, and automate repetitive data transformation tasks.

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