Data quality
Data needs to meet the process quality requirements to make them operate efficiently. Then there are many exception flows in the business processes that go around the usual happy flows data is created. This results in gaps in the data quality further down the process chain.
Monitoring these data quality gaps is essential for a continuous process. There are many software vendors that promise you the best data quality analysis & reporting solutions. At a notable price of course.
The real cost is the time and effort it takes to identify & define the rules that need to applied on the data to meet these requirements. This requires close interaction between the process expert and the data analyst. This is a lengthy process before data quality measures can be built into the data quality reporting environment.
What when where how data quality?
So first we need to understand what data quality is. Lean Data defines data quality as:
The degree to which data meets the requirements of the processes it is used in
When we look at data the data management body of knowledge (DMBOK) gives us 6 dimensions that represent data quality: So this sounds easy and you may feel you can start right away. The challenge is to find those deviations in your data that affect your organisation. Lean Data uses 4 categories to determine whether a deviation in one of the 6 dimensions is worth to spend time and effort on:
When a deviation in your data affects one of these impact categories you should make this a priority in documenting the business rules. For the business rules you can try to define data quality rules and implement those as mitigations. These mitigations should be implemented at the source where data is created. This should enable you to prevent these deviations affecting your organisation in the future.
Find your data deviations
Lean Data has developed an easy to use data deviation exploration solution that runs on your desktop environment. It is purpose built to help you define business rules for the first 5 data quality dimensions.
- No installation of software
- No IT purchasing approval processes
- No IT change management & upgrades
- No vendor lock-in
- No need going back and forth with requirements and development time