Data Quality
Better decisions. Better results.
Overview
Data Quality Matters. It drives the quality of your entire business. How well you know your customers, what they buy, how often they buy it, what they would like, the correct price point and so much more is driven by data quality.
Those that invest in high quality data with enforced standards, QC and procedures get good results. Those that don't will reap the inverse and have messy data. You get to choose. Choose wisely, you will reap what you sow.
Key Concepts
The most important attributes of data quality.
Complete
The data set is actually complete and isn't missing values that should be there. Some values can be missing, but those that can't should be there.
Consistent
The data set is consistent among itself. It doesn't use unknown acronyms and terms are recorded the same way every time. If not done this was it affects reporting, queries and lowers performance of technology products.
Accurate
The data set accurately reflects data from the real world. An example would be an address that is out of data for an order would be inaccurate data.
Timely
The data set is actually up to data at the time it is needed. If it takes weeks to update a data set it isn't timely. Automated programs can help with this.
Unique
Each record in a data set is unique and not a duplicate of another record. While some fields may be duplicated a complete record that is duplicate should be deleted.
Valid
The data set is within acceptable values according to business rules. So if a field takes values that are integers from 1 - 10 both -3 and 7.4 would be invalid values.