Credits: None available.
• Creating quality control models to ensure data is properly sourced, contains required elements for assigned function and is monitored for consistency of results
• Strengthening data quality with centralized data stewardship to standardize governance, curtail duplicative data harnessing and coordinate training policies
• Conducting quality assurance testing to analyze data integrity and take corrective actions such as increased automation of data processing as needed while safeguarding data
You must be logged in and own this session in order to