Validation of data is essential to ensure that the data is correct, clean, and useful. A company needs to have accurate information about the customer. Any data collected using different tools should be cleaned before being recorded. In this way, you can take decisions based on realistic assumptions about the customers. Here we will take a brief look at the process of data validation.
Data validation is a process that ensures that the collected data is clean. The aim of the data validation process is to ensure validity and integrity of the data. This ultimately assures the quality of the data that will help in improved decision making.
The data validation occurs at different levels. The three main stages where the data validation process occurs include the following.
· Collections of Data
Validation first occurs during the data collection stage. Verification of forms is much easier in case of electronic documents. The form mentions questions that are mandatory. Before submission, the software checks whether all the forms are filled. Also, some software look at the format of the response. A user won't be able to submit a form unless for instance the credit card number, date, or phone number is written in the correct format.
The data should also be verified when it is being stored. Prior to storing the data, it must be verified that there are no duplicate forms. Databases are particularly sensitive to redundancies. Again, this is important to ensure the quality of the collected data.
· Organization of Data
Validation should also occur when the data is being organized. At this stage, the data should be checked for inconsistencies and errors. It is important to ensure that the data does not contain incorrect or irrelevant information.
The data verification process itself is entirely objective. It ensures that the collected data correctly represents the reality. The methodologies that are involved in verification of data include checking the information twice or more times to avoid any error or fraud. Also, the electronic signatures can be checked to verify the authenticity of the document. In case the hash value of the document stored in the public key does not match, the system will show an error message.
Manually verification of data is expensive and time-consuming. Looking at the digital imprint by analyzing the e-signature is an effective data verification methodology. The method ensures that the content of the document has not modified in any way, and the responses represent views of the original signatory.