What is data transformation?
data transformation is the process of converting information or data from one format to another format. While the strategy is often considered to convert documents from one format to another, data transformations may also include transfer of programs from one type of computer language to another format to allow the program to run on a specific platform. The actual transformation may include the transfer of multiple data flows to a common format or convert one format to several different forms for use across a wide range of platforms.
The data transformation process involves the use of what is called SQL or the structured language of queries. SQL is a computer language that is responsible for managing information that is in a certain type of data management system. One of the oldest languages used in the modern program design, SQL data transformation allows you to connect data across several programs to manage data efficient into formats that each of the associated programs can recognize.
In the actual use of data transformation, it includes the use of a executable program that is able to read the basic or original language of data, and identify the language or languages into which data must be translated in order to use other programs. Once the transformation mapping is made, the program then converts the data to the required or more required formats and corresponds to the converted data corresponding appropriately. With many applications, this happens in seconds.
The process is known as data mediation. Like data transformation, it is the idea that data in one format can be applicable in another format. One of the differences with the mediation is that the data mapping process involves the creation of what is known as a data model, serving as intermediary two participating formats, rather than a direct translation that occurs with information transformation.
as well asIn many types of computer technology, data transformation is a process that is constantly evolving because new programs help increase the efficiency and extent of how information can be translated. Since multiple programs and formats include this process, the ability to share data on many different platforms that were once completely incompatible has increased significantly. In a global environment where collaborators do not always have to use the same programs or languages as the basis for their data systems, this continuous improvement means significantly less time devoted to manual translation and data entry between systems.