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Data Mapping is a process that allows data elements from one datasheet to be linked to data elements in a target destination or storage. The process is commonly used in data management to facilitate data integration, migration, and transformation. In simple terms, Data Mapping helps in moving data from one place to another without necessarily changing the nature of the data.
Data Mapping usually takes place in three steps:
During mapping, data elements are matched based on their characteristics like names, data types, and formats. Once the data mapping is completed, the data is ready to be transferred or transformed to its target destination or storage.
Data Mapping is an essential process in data integration and management. It helps organizations in:
The process of data mapping reduces the risk of data loss, errors, or inconsistencies during data transfer. It allows organizations to maintain data quality and integrity, leading to better business decisions.
Data Mapping has numerous use cases that are relevant to modern businesses. Some of the most important use cases include:
There are other technologies and terms that are closely related to data mapping:
Dremio users would be interested in Data Mapping because it plays a critical role in Data Integration and Data Transformation. Dremio's data lakehouse platform allows organizations to integrate and transform data from various sources and store it in a single platform. Data Mapping helps organizations to maintain the consistency of data during these processes, ensuring that the data loaded into Dremio remains accurate and reliable. Furthermore, Dremio's built-in Data Catalog allows users to map their data quickly and efficiently, improving the speed and accuracy of data analysis.