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1
- Introductions
2
- Key Axes of Data Quality
3
- What is Data “Fitness”
4
- Data Fitness: Validity
5
- Data Fitness: Reliability
6
- Data Fitness: Representativeness
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- Remediating a lack of Data Fitness
8
- Conclusion
Description:
Explore the critical aspects of data quality assessment in this informative talk by renowned data science expert Susan McGregor. Delve into the three crucial facets of data "fitness" to ensure your data is suitable for its intended purpose. Learn how to identify gaps and errors, unlock the true potential of your data, and gain invaluable insights for data science professionals. Discover techniques for remediating a lack of data fitness and understand the key axes of data quality. Unravel the complexities of data integrity problems and empower yourself to harness the full potential of your data to answer pressing questions in your field.

Assessing Data Quality - The 3 Facets of Data Fitness

Open Data Science
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