Optimal Work Daily - Career, Productivity and Entrepreneurship 1917: What is Data Quality and How Do You Measure It for Best Results by Sherice Jacob with Neil Patel on Data Standards
Dec 30, 2025
Explore the intriguing world of data quality as misconceptions are debunked. Learn why relevance and consistency matter more than perfection. Hear about the vital role of data stewards in setting quality standards. Discover how to balance accuracy with costs, and the significance of data profiling to identify issues. Sharice Jacob shares practical strategies for error management and data integration. Plus, get introduced to six essential dimensions of data quality for effective business decisions.
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Quality Over Perfection
- Data quality doesn't require perfection; it must meet defined standards and tolerances.
- Balancing accuracy, completeness, speed, and cost is the core challenge for effective data quality.
Start With Data Profiling
- Profile your data to discover accuracy, completeness, duplicates, and formatting issues before acting.
- Use profiling as the baseline to decide whether to accept, reject, correct, or default problematic entries.
Decide A Clear Error Strategy
- When you find bad records, choose one of four actions: accept, reject, correct, or set a default value.
- Define tolerance levels so small variations (e.g., 'Main Street' vs 'Main St') can be accepted without blocking workflows.