EN – Data Quality
Our decisions will only be as good as the information we use to make them.
Nuestras decisiones serán tan buenas como la información que usamos para tomarlas.
Data quality in decision making
According to a Gartner report, 0% of companies do not measure the annual financial cost of having a poor quality database.That report also tells us that the average cost to companies for not investing in Data Quality tools in the cloud averages $15,000,000 per year.
Storing large amounts of data can lead to databases that include poor quality data. But not only the volume of data but also the disparity and silos of information directly impact the quality and consistency of corporate information.
The information is stored without prior review and without checking whether we already have the data, whether it is written correctly or whether it is in the correct format.
Poor quality data is not operational or reliable and can harm your organization’s decision making based on incorrect data.
In order to comply with the current legislation GDPR or LOPD among others, the data must be aligned with the necessary quality requirements.
- Data Quality is focused on the use and status of data. The quality of information is ensured through processes such as standardization or intelligent use of data quality.
- Find and fix erroneous, inconsistent or differently formed data and provide the best experience for your customers.
- Check at all times that the data stored is fit for purpose, accurate, reliable and always up to date.
- Members of your organization will have the best user experience using cloud tools that provide consistency and accuracy in data management.