More and more business leaders understand the importance of data. However, data quality remains an unexploited and unfairly underappreciated area. We explore what data quality really is through 3 myths and a truth about data quality in the business environment.

In today's world, business decisions —actually, any kind of decisions— are data-based. However, having a lot of data does not necessarily mean making a lot of good decisions. In this case, as in so many others, quality comes before quantity.

Two years after the implementation of the GDPR, many companies are still not complying with the protection of personal data rules. The regulatory framework has taught us a lesson in data quality and data governance that companies can no longer ignore.

Cross-selling and up-selling are two types of business intelligence strategies that are becoming increasingly popular among companies. Their growing popularity is due to their proven efficiency in increasing companies' profitability and the average value of the purchase ticket. In fact, these are their aims, but[...]

Data quality is a measure of the status of data that is based on several factors: accuracy, consistency, and reliability, among others. Measuring data quality levels can help organizations identify mistakes that need to be resolved and assess whether the data in their computer systems is fit for the purpose for which[...]