Human error, failed tasks, the use of confusing information, and poor data collection practices are one of the most prominent reasons why bad data can threaten your database. Additionally, associations that store and manage their data in multiple systems are more prone to facing data health issues. In multiple cases, raw data collected is originally […]
According to reports on average, companies around the globe function with the fear that around 26% of their data is dirty. This collection of bad data in their systems results in losses of around 15% to 25% on revenue. Every year US economy approximately faces a $3 trillion loss. Dealing with dirty data doesn’t only impact […]