Data is everywhere, but it doesn’t mean much in its raw form. Even if the process isn’t part of your job, data transformation is essential for leveraging all this information. In a world where data is constantly being collected, stored, and analyzed in many forms, understanding the steps it takes to transform data from one form to another can be extremely useful.
In this article, we’ll explain the data transformation process in four easy steps.
Data Transformation Defined
Data transformation is the process by which data is converted from one format to another. For instance, data may be taken directly from a database file and converted into an Excel spreadsheet. Typically, the data transformation process involves taking a raw data source and putting it into a cleansed, validated, and ready-to-use format.
Data transformation is an essential part of data management processes like data integration, data migration, data warehousing, and data preparation. It is also a crucial component for any organization that wants to leverage data for timely business insights.
The Data Transformation Process In Four Steps
The exact data transformation may vary by situation, but these four steps are the most common parts of the data transformation process.
The first step in data transformation is interpreting the data. You’ll need to determine what type of data you currently have and what you’d like to transform it into. Data interpretation is a little more difficult than it seems at face value.
Data interpretation relies on assumptions about data formatting based on the extensions attached to a file name. If you’ve ever saved an Excel spreadsheet, you’ll likely have seen the .exe file extension or the .docx extension for a Word file. Problems pop up because the data inside a file doesn’t always match the file type indicated by the extension.
When saving files, users can add any extension to the file name or remove it completely. Since data interpretation requires a deeper look, it requires proper tools that can analyze the structure of a database to see what is inside. Modern software programs like Procoto make it easy to store data and interpret data to facilitate the data transformation process.
Pre-Translation Data Quality Check
After you or your data transformation tool have determined what kind of data formats you’re working with and what form you’d like your output to be in, you need to run a data quality check. Performing a data quality check allows you to identify potential problems like missing or corrupt values in a database or source data. This can create issues in the later parts of the data transformation process.
The third step in the data transformation process is data translation, which begins after the quality of the source data has been checked and maximized. Data translation is when you take each part of the source data and replace it with new data that fits within your target format’s requirements.
For instance, you may need to translate an HTML file that was written in an outdated version into HTML5, which is the most modern version Web browsers expect. In the translation process, deprecated HTML tags would need to be replaced with those that are supported by the latest standard of HTML.
Post-Translation Quality Check
The final step in the data transformation process is the post-translation data quality check. In this step, you are once again optimizing your data by looking for inconsistencies, missing information, or other errors that may have been introduced before the data translation step. Even the cleanest data stands a good chance of developing an issue during data translation.
Reasons to Transform Data
We are living in an increasingly data-driven world, and organizations need to be able to mine their data for insights in order to successfully compete in a digital marketplace. These data insights can help you optimize operations, cut costs, and boost productivity. Data transformation is also needed to feed systems that use AI, machine learning, natural language processing, and other advanced technologies that lead to better efficiency and productivity.
Data transformation plays a big role when an organization must combine or switch systems by ensuring that the data from one is compatible with the other. If an organization is acquired or switching to a cloud-based system, the data transformation process is important to preserve all the legacy data.
Tools for Data Transformation
If you work in data transformation, there are many tools on the market that can support the process. These tools technology to automate many of the steps within the data transformation process and can replace much of the manual scripting and hand coding that has long been a major part of data transformation.
Of the many data transformation tools out there, some are designed for on-premises transformation processes and others are made for cloud-based transformation activities. While there are some data transformation tools that only deal with the data transformation process, there are many tools on the market that also offer a broad range of capabilities for managing enterprise data and streamlining operations. One such tool is Procoto.
Better Data Transformation With Procoto
Not only is Procoto a great tool for data transformation and smart databasing, but it is also a comprehensive platform with tons of convenient features for your organization’s sourcing needs. Procoto solves common business challenges by providing more data for better leverage, deeper insights into sourcing progress and key information, streamlined sourcing, and all-in-one systems for vendors, contracts, and purchasing.
In addition to creating a more streamlined and informed strategic sourcing department, one of the best benefits of Procoto is that it is a cloud-based program. Your team can work from any location with an internet connection, meaning you can embrace the current trend of remote and hybrid work models or use one system for employees spread out across different locations. Procoto is safe, secure, and has everything you need to transform your data and your business.
Partner With Procoto
The data transformation process is easy with the right partner. If you’re ready to hear more about how Procoto can help you make the most of your data, get in touch with us today.