Data requires ongoing upkeep to remain in the best condition for analytics. Monitoring data’s accuracy, completeness, timeliness, and other quality measuring metrics ensure the information used in data-driven decisions is the best it can be. Learn what to look for when examining data quality, how to fix it, and ways to prevent poor quality data in the first place.
Topics include a high-level and strategic look at:
- Understanding Data Quality Holistically
- Measuring Data Quality
- The Data Quality Improvement Lifecycle
- Master and Reference Data Management
- Third-Party Data Quality Governance
