Data transformation

In computing, data transformation refers to the process of changing data from one format or structure to another format or structure using computer programmes. It is a crucial component of the majority of data integration and data management jobs, including data wrangling, data warehousing, data integration, and application integration, among others.

When it comes to data transformation, it may be simple or complicated depending on the changes that need to be made to the information between the source (initial) and the destination (final). Data transformation is often accomplished using a combination of human and automated procedures. Based on the format, structure, complexity, and amount of the data being translated, the tools and technologies that are used for data transformation might differ significantly.

Master data recast (or master data transformation) is another kind of data transformation in which the complete database of data values is modified or recast without removing any data from the database itself. A network of foreign key constraints connects all of the data in a well-designed database to a small number of master database tables, which are themselves linked to a smaller number of master database tables. Each foreign key constraint is reliant on a unique database index from the parent database table in order to function correctly. Consequently, when the appropriate master database table is recast with a new unique index, all of the directly and indirectly associated data is likewise recast or restated in the process. The data that is directly and indirectly associated to the master data may still be examined in its original form since the original unique index is still present with the master data. Furthermore, the database recast must be performed in such a manner that it has no influence on the software that governs the application design.

When the data mapping is done indirectly via the use of a mediating data model, the process is referred to as data mediation.