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Duration 7 hours
Course Outline
Introduction
Overview of Data Cleaning
- The significance of data cleaning
Case Study: Managing Dirty Big Data
Crafting a Comprehensive Data Cleaning Strategy
Essential Data Cleaning Tools
- Drake
- OpenRefine
- Pandas (for Python)
- Dplyr (for R)
Ensuring High Data Integrity
- Completeness
- Correctness
- Accuracy
- Relevance
- Consistency
Automation of Data Cleaning Processes
Monitoring Data Cleaning Systems
Summary and Conclusion
Requirements
- Foundational knowledge of data analytics concepts.
Target Audience
- Data Scientists
- Data Analysts
- Business Analysts
Testimonials (2)
Using Road Safety data when doing praticals
Maphahamiso Ralienyane - Road Safety Department
Course - Data Cleaning
It was insightful and I gained a lot of data analysis skills