Definition and the importance for companies

Data plays a critical role in the success of a business, and especially in today’s digital era more than ever. Whether it’s customer data, financial information or business transactions, the accuracy and reliability of the data is paramount. This is where the term “validation” comes into play. Validation refers to the process of checking and confirming the accuracy, completeness and consistency of data. In this article, we will go into more detail about what validation means and why it is so important for businesses.


The word “validate” comes from the Latin word “valere” and means something like “to establish the value of something.” Data validation involves checking data for compliance with certain validation rules. The validation rules are defined in advance and include, for example, specifications on formats and value ranges. Data validation improves the results of data processing and data analysis.

In computer science, “validation” describes a process of checking and confirming the correctness, completeness and consistency of software, data or systems. The purpose of validation is to ensure that a product, application, or system meets specified requirements, standards, and expectations. Various tests, analyses and procedures are used for this purpose. Validation is an important step in the development process to ensure that the software or system fulfills its intended purpose and operates without errors.

What is the importance of data validation for companies?

Data validation is critical for businesses for several reasons. First, it ensures the quality assurance of your data. By checking for accuracy, completeness and consistency, you can ensure that your data is of high quality and provides a solid foundation for making informed decisions.

Another important aspect is error detection. By validating your data, you can identify and correct errors and inaccuracies early on. This minimizes the risk of wrong decisions and improves the accuracy of your analyses and forecasts.

Data validation also plays a key role in meeting compliance requirements. By ensuring that your data meets regulatory requirements, you can avoid legal consequences and improve risk management.

Last but not least, data validation helps improve customer relationships. By validating customer data, you can run personalized marketing campaigns, provide tailored customer service, and increase customer satisfaction.

Validation in the field of data processing

In the field of data processing, application errors or even incorrect results can occur under certain circumstances without validation. For this reason, validation of data is a basic requirement for correct and meaningful data processing. Data validation can vary from use case to use case and can be performed at various stages of data processing, including data input, processing, and output. Validation can be automated or manual, depending on the nature of the data and the specific requirements of the business. Ideally, validation is performed in real time to detect and correct errors or problems as early as possible. 

DocBits, a breakthrough invoice and document capture solution, can revolutionize the way your organization manages its data. Its advanced features, seamless integration and user-friendly interface make DocBits an indispensable tool for companies looking to streamline their processes and stay ahead of today’s competition.

However, simply extracting data does not make a document accurate or valid. By integrating DocBits with Infor, multiple data validations are performed to ensure the validity of the document’s content. Verify your vendor or customer information and bank details. Reconcile your documents with a purchase order in Infor. Trigger approval workflows to collaborate as a team.


In summary, data validation is critical to ensuring the quality, integrity, and reliability of data. It enables informed decision-making, secure analytics, and efficient business execution. By performing validation, organizations can improve the accuracy of their data and increase confidence in their database.


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