Data Mapping

What is Data Mapping?

Data mapping is the process of matching data fields from one source to data fields in another source. It helps ensure that data from one source can be accurately and effectively transformed or transferred to another destination while maintaining its integrity, consistency, and meaning. Data mapping is the initial step of any data process, including ETL and data integration.

Data Mapping Process

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Data Mapping Example

Usually, source data is directed to either a relational database, data warehouse, or any file, like a CSV document — depending on the use case. In most cases, companies use a data mapping template to match fields from one database system to the other using a data mapping solution.

Source-to-target mapping integration tasks vary in complexity depending on the data hierarchy and the disparity between the structure of source and target data. Whether on-premise or cloud, every business application uses metadata to explain the data fields and attributes that constitute the data and semantic rules. These rules govern how data is stored within that application or repository. The goal is to ensure a seamless transfer from source to destination without any data loss, and the data mapping process plays a key role in this aspect.

For example, Microsoft Dynamics CRM contains several data sets with different objects, such as Leads, Opportunities, and Competitors. Each of these data sets has several fields like Name, Account Owner, City, Country, Job Title, and more. The application also has a defined schema along with attributes, enumerations, and mapping rules. To add a new record to the schema of the data object, the user will have to create a data map from the source fields to the Microsoft Dynamics CRM account.