What is data mapping?
Data mapping is the process of linking data and matching data fields from one source to a target system. It identifies the data in the source system, understands how it relates to the data in the target system, and creates a mapping that describes how the data should be transformed and moved from the source to the target.
Data mapping is used to integrate data from various systems, such as point-of-sale systems, inventory management systems, and customer relationship management systems.
Example of how data mapping works
Consider the scenario where a retail company utilizes a product information management system (PIM) and a point-of-sale (POS) system. The PIM system is responsible for managing product content, while the POS system handles sales transactions.
When these systems need to share data, data mapping facilitates the alignment and integration of product information. For instance, the POS system may record sales transactions with product attributes represented as a single string, such as 'Shirt - Blue - Small.' On the other hand, the PIM system requires separate fields for product name, color, and size, and as such may not recognize the data format used by the POS system.
Data mapping bridges this gap by establishing rules that transform the data from the POS system into the desired format for the PIM system. In this example, data mapping would split the single string into separate fields, extracting 'Shirt' as the product name, 'Blue' as the color, and 'Small' as the size. This ensures that the data is properly aligned and formatted for each system, enabling seamless integration and accurate information flow between the PIM and POS systems.
By incorporating data mapping, the retail company can maintain consistent and synchronized product information across systems, ensuring accurate inventory management based on sales transactions recorded in the POS system.