The Difference Between Data Transformation and Data Translation

What is Data Translation?

Data translation can be defined as the process of converting volumes of data from one syntax to another and performing value lookups or substitutions from the data during the process.  Translation can include data validation as well. One example of data translation is to convert EDI purchase order document data into purchase order database files or even flat files while performing data validation on the source data.

Data Translation is the process of converting data from the form used by one system into the form required by another.

What is Data Transformation?

Data transformation is the process of converting data from one format to another, typically from the format of a source system into the required format of a destination system. Data transformation is a component of most data integration and data management tasks, such as data wrangling and data warehousing.

An example of a data transformation tool is routing a purchase order to a specific process that will perform a data translation to convert the shipping and billing address information to an invoice document.  We can also use the translation example from above, transforming an EDI purchase order to a database and then during this transformation, also perform additional processing using formulas such as determining a total number of items or total dollar amount by looping through specific data constructs.  Other actions that can be performed during the data transformation process include invoking web services and calling a process.  Another transformation example may be to convert character data from one character-encoding scheme to another.

A data transformation tool is not only used for data translation, but a lot more. Data translation is limited to data operations, whereas data transformation combines data operations and process control in a single model.

Via cleo.com