Data Transformation
Definition - What does Data Transformation mean?
Data transformation is the process of converting data or information from one format to another, usually from the format of a source system into the required format of a new destination system. The usual process involves converting documents, but data conversions sometimes involve the conversion of a program from one computer language to another to enable the program to run on a different platform. The usual reason for this data migration is the adoption of a new system that's totally different from the previous one.
Techopedia explains Data Transformation
In real practice, data transformation involves the use of a special program that's able to read the data’s original base language, determine the language into which the data that must be translated for it to be usable by the new program or system, and then proceeds to transform that data.
Data Transformation involves two key phases:
Commonly used transformational languages:
Data Transformation involves two key phases:
- Data Mapping: The assignment of elements from the source base or system toward the destination to capture all transformations that occur. This is made more complicated when there are complex transformations like many-to-one or one-to-many rules for transformation.
- Code Generation: The creation of the actual transformation program. The resulting data map specification is used to create an executable program to run on computer systems.
Commonly used transformational languages:
- Perl: A high-level procedural and object-oriented language capable of powerful operations
- AWK: One of the oldest languages and a popular TXT transformation language
- XSLT: An XML data transformation language
- TXL: A prototyping language mostly used for source code transformation
- Template Languages and Processors: These specialize in data-to-document transformation
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