In recent years most organizations have fixated on improving data quality, and although many have made great strides, there is still room for improvement.
One of the major hindrances holding corporations back from further improvement are the myths and misconceptions about what makes up an effective data quality strategy.
This informative paper takes a look at the top 7 data quality management myths and provides practical tips on how to design an effective data quality management strategy.
Myths debunked include:
- Monitoring and reporting data quality does not eliminate errors
- Manufacturing quality practices are easily applied to data
- The business is responsible for data quality
- And more.