Elite Edition
Data Cleaning Strategies
Issue #24 | Aug 23
Business Analytics Newsletter
· 3 min read
Issue #24 | Aug 23
Hello!!
Welcome to the new edition of Business Analytics Review!
We hope you enjoyed our previous newsletter on Exploratory Data Analysis! It was all about summarizing the main characteristics of a dataset with visual methods and discovering patterns.
In this edition, we’re diving into the world of Data Cleaning Strategies. Data cleaning strategies refer to the methods and techniques used to identify, correct, or remove inaccuracies, inconsistencies, and errors in data. Data cleaning allows you to improve the quality of data, making it accurate, complete, and ready for analysis or processing.
Data Cleaning
Handling Missing Values: Tackling empty cells.
Outlier Detection: Identifying and dealing with unusual data points.
Data Imputation: Filling in missing values with estimated values.
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