Data Quality Management (DQM) is one of the very important implementation components in an Enterprise Data Management (EDM) initiative. Following are few definitions to be noted in the context of a DQM process.
- Exceptions – These are errors determined on the Data
- Checks – These are rules that are applied over the data to capture the Exceptions
- Data Quality Management – The end to end process of managing the Exceptions identified by applying the Checks over the data can be called Data Quality Management
The core solution components of a DQM setup that addresses data quality issues in an enterprise can be quite generalized across industry, they are
- Data Capture & Profiling
- Exception Detection
- Checks Management
- Exception Checks
- Exception Handling
- Exception Resolution
- Exception Reporting
Following table summarizes what these components deliver functionally and the technology platforms that will be required for the implementation of these components.
|Solution Component||Key Functionalities Addressed||Technology|
|Data Capture & Profiling||
The above solution components and the functional requirements can be a checklist for a DQM solution. Also need to note that to meet the requirements of a DQM solution, multiple technology platforms covering data integration, ticketing application, reporting and custom applications are to be integrated, there isn’t single platform that meet all the requriements.
Thanks for reading, let me know your thoughts on the DQM requirements and solution components…