Data mapping is a process used in computer programming and system architecture in which complex data is coded for storage and retrieval in a database. It is the process of organizing complex datasets into logical, hierarchical structures that can be easily accessed and manipulated. The logical structures can be seen as a map of the data, which makes them highly useful.
Data mapping is often used in business intelligence and data warehousing applications. It can help organizations make more effective decisions by transforming raw datasheets and databases into more structured and useful datasets that can be used for analysis. Data mapping can also be used for data replication, synchronization, and migration between databases.
Data mapping involves transforming data from one format to another. For example, data can be mapped from a flat-file database, such as Microsoft Excel, into a database with multiple tables and relationships. This process may incorporate the use of data mapping standards, or logical data models, to ensure the data in the new format is as accurate as possible.
Data mapping can also be used to simplify business processes. For example, data mapping can be used to reorganize customer information from multiple sources into a single customer record. Once this data is mapped and stored in a consolidated system, business processes can be automated, such as notifications when a customer’s marital status changes.
Data mapping is an important step in the software development process, as it helps define the relationships between databases and provides a cohesive view of data. It also helps to ensure data accuracy, consistency, and quality. By effectively mapping data, organizations can take advantage of more structured datasets and more powerful analytics.