Between the Spreadsheets - Classifying and Fixing Dirty Data for Data Science

Explore real-world examples of dirty data and its impact on decision-making, reporting, analytics, AI, and machine learning in this 58-minute video presentation by Susan Walsh. Learn quick and accurate methods for checking and modifying data in Excel, regardless of experience level, while understanding the importance of data accuracy and maintenance. Discover best practices for identifying anomalies and implementing effective data cleanup processes to transform and elevate your data analysis skills. The presentation covers topics such as defining dirty data, its consequences, ensuring data accuracy, maintaining and spot-checking data, exploring other tools, understanding the dirty data maturity model, and concludes with a summary and Q&A session.

Introduction
What is dirty data
The consequences of dirty data
Ensuring data accuracy
Maintain and spot-check your data
Other tools
The dirty data maturity
Summary
QnA