What is Data Transformation?

Data transformation is the process of validating and normalizing business data as it is acquired in order to maintain quality and facilitate usability in downstream applications and processes such as business intelligence.

What do I need to know about data transformation?

Data transformation primarily involves mapping how source data elements will be changed (or transformed) for the destination. This makes it possible to transfer data from one type of file system to an entirely different type without manual effort. Data transformation is written in specific programming languages, often Perl, AWT, or XSLT. 

What are the benefits of data transformation?

Data transformation ensures that data that enters your enterprise is usable and manageable. It facilitates cost-efficient storage, ease of analysis for greater business intelligence, and operational efficiency.  On the flip side, storing data that has not been transformed wastes resources and creates the possibility of compliance risk because the data cannot be managed under the organization’s data governance rules. 

How is data transformation accomplished?

Commercial data transformation packages are available to help minimize the effort needed to transform data. These provide preprocessing and libraries that can analyze the source data and automate or suggest the best mapping schema. A graphical user interface makes it possible for administrators to evaluate and adjust the mappings without writing code.

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