How the Data Transformation Process Works

As your business grows and evolves, so do the volumes of data formats and applications you must also support. Whether an enterprise is trying to onboard a new trading partner or ensures that it meets all the requirements a customer has, information is coming from many different places.

The last thing your enterprise wants is to be difficult to do business with. You need to be able to communicate efficiently with the members of your digital ecosystem in order to expand and take on more customers. That’s why efficiency in the data transformation process is so valuable to an organization:  companies that can handle formats of any size, shape, or form are the ones that are going to thrive in the age of the cloud.

What is Data Transformation?

Data transformation is the process of converting data one format, whether it’s a database file, an XML document, or something else, to another. The data transformation tools and techniques are critical because information can reside in many different locations and formats, and enterprises must have the ability to convert data depending on the unique needs of its business ecosystem. The end goal of data transformation ensures data is readable when it moves from one application, or data warehouse, to another.

Occasionally and also important to note, it is possible that some information needs to be cleansed before it is actually transformed. Data cleansing takes the data and prepares it for transformation because it removes any inconsistencies, errors, or missing values. From there, the data is ready to be transformed.

How the Data Transformation Process Works

Here are some steps in data transformation: 

Throughout a data transformation procedure, a number of steps must be taken in order for the data to be converted, made readable between different applications, and modified into the desired file format.

Step 1 - Data Discovery

The first step in the data transformation flow begins when you identify and truly understand the information within its source format. Data profiling tools do this, which allows an organization to determine what it needs from the data in order to convert it into the desired format.

Step 2 – Data Mapping

The data mapping phase of the data transformation flow lays out an action plan for the data. Data mapping is often the most expensive and time-consuming portion of an integration strategy because it encompasses  validation, translation, value derivation, enrichment aggregation, and routing.

Step 3 – Code Generation

When information must be converted, a code must first be created that actually runs the data transformation “job.” Centralized integration platforms are able to generate the code to simplify the task for enterprises.

Step 4 – Code Execution

Once the code has been created and the data transformation procedure is fully planned, it’s time to execute the code. The code is put into motion and converts the data to your desired output.

Benefits of Using Data Transformation Software

Data transformation tools and techniques have become such valuable resources for today’s enterprises that the question becomes where can you find the technology to handle all of this data? A centralized integration platform that provides any-to-any transformation tools and mapping solutions with an engine to fully automate the connection, transformation, and integration of business-critical data warehouses would be ideal.

Data transformation software available in the Cleo Integration Cloud platform makes the process much easier because it allows you to quickly grow business opportunities with EDI and non-EDI transformation. Cleo Integration Cloud gives enterprises the ability to:

• Support end-to-end processes by creating one-to-many ecosystem data exchanges between any internal system, cloud, and trading partner application utilizing EDI, XML, or APIs
• Drive information efficiency and eliminate integration process bottlenecks by consolidating integrations to a single, easy-to-use platform
• Automate mapping and reduce the time and cost of building and maintaining data transformation software and mapping processes

Cleo Integration Cloud accelerates any-to-any integration because it can transform the data into any format from any application or trading partner source while automating validation, transformation, and orchestration processes.

Learn how the Cleo integration Cloud platform can address your integration and business needs today.

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