Validating the data ensures that the data is accurate, which means all systems relying on a validated given data set will be as well.ĭata validation is also important for data to be useful for an organization or for a specific application operation. These operations can include machine learning or artificial intelligence models, data analytics reports and business intelligence dashboards. The output of any given system can only be as good as the data the operation is based on. Why validate data?įor data scientists, data analysts and others working with data, validating it is very important.

Data validation can be a component to measure data quality, which ensures that a given data set is supplied with information sources that are of the highest quality, authoritative and accurate.ĭata validation is also used as part of application workflows, including spell checking and rules for strong password creation. Each type of data validation is designed to make sure the data meets the requirements to be useful.ĭata validation is related to data quality. It can also be used to ensure the integrity of data for financial accounting or regulatory compliance.ĭata can be examined as part of a validation process in a variety of ways, including data type, constraint, structured, consistency and code validation. Data validation operation results can provide data used for data analytics, business intelligence or training a machine learning model. Data validation is the practice of checking the integrity, accuracy and structure of data before it is used for a business operation.

Mac excel 2013 data validation