January 2025
Intermediate to advanced
436 pages
11h 10m
English
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1.4 What Could Go Wrong?
In real-world data analysis, particularly in customer segmentation and healthcare data projects, several challenges and pitfalls can arise. Below are some common issues to be aware of, along with solutions to help mitigate them.
1.4.1 Poor Data Quality
Real-world datasets often contain missing values, duplicates, or inconsistencies, which can lead to inaccurate results if not handled carefully. Issues like data entry errors, missing demographic details, or mislabelled records can significantly impact analysis outcomes.
What could go wrong?
- Missing or incorrect data can skew insights, leading to unreliable customer segments or health-related predictions.
- Duplicates may inflate certain patterns, creating misleading conclusions ...
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