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 Duration 7 hours

Course Outline

Introduction

Overview of Data Cleaning

  • Understanding the significance of Data Cleaning.

Case Study: The Impact of Dirty Big Data

Crafting a Comprehensive Data Cleaning Strategy

Essential Data Cleaning Tools

  • Drake
  • OpenRefine
  • Pandas (Python)
  • Dplyr (R)

Ensuring High Data Integrity

  • Completeness
  • Correctness
  • Accuracy
  • Relevance
  • Consistency

Automating the Data Cleaning Workflow

Monitoring the Data Cleaning System

Summary and Conclusion

Requirements

  • A foundational understanding of data analytics concepts.

Target Audience

  • Data Scientists
  • Data Analysts
  • Business Analysts

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