Companies today are gathering enormous amounts of data through various initiatives and digital transformation projects. As a result, data analysis activities are expected to have a positive impact on their revenues, margins and organizational efficiency. However, before analytics can be of any value, the data must be of high quality. Businesses can now foresee the importance of keeping their data clean. Maintaining data quality is a painful process, it involves tedious steps from setting criteria of creation, rules for standardization, integration, etc. which should be resonating with business requirements.
Within MDO, data quality workbench provides a health check for the organization master data. It checks the data for duplicity, completeness, accuracy and validness. This work bench displays all the data rules running for the user data. Admin can set-up data quality checks from a pre-defined set of rules or create their own rules and stay on the top of its important data.