Data mapping is the process of matching data fields or elements from one database to another. Data mapping also helps consolidate data by extracting, transforming, and loading it to a destination system. Data mapping is a key part of data management and data integration.
Data mapping bridges the differences between two systems, or data models, so that when data is moved from a source, it is accurate and usable at the destination.
It is the translation of information between source and destination, such that the logical/semantic meanings are kept intact and the fitness of use of the destination data is enhanced.
During the data mapping process, the source data is directed to the targeted database. The target database can be a relational database or a CSV document — depending on the use case.
Data mapping allows the user to organize, distill, analyze, and understand vast amounts of data that live in various locations so he can draw conclusions and insights.
Data mapping has been a common business function for some time, but as the amount of data and sources increase, the process of data mapping has become more complex, requiring automated tools to make it feasible for large data sets. Data mapping is used in a range of use cases and industries to streamline data processes.
Data mapping
A computer system comprises hardware and software components, aiming to offer a powerful computational tool. These systems play a crucial role across diverse domains, aiding us in numerous tasks. The prevalence of the internet has significantly bolstered the utilization of computers for information sharing and communication. Computer systems empower us to store, process, display, and transmit information. Even in a basic modern computer system, multiple programs are typically required to carry out various functions effectively.
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