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Data cleaning process in SQL on a global dataset of company layoffs to ensure accuracy and consistency for analysis

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Global_layoffs

A data cleaning process applied to a dataset related to companies' layoffs around the globe.

The purpose is to show the cleaning process normally applied to datasets, including some SQL skills.

  1. Remove duplicates (CTEs, Copy/create tables)
  2. Normalise data (Trim, Trim Trailing, working with dates, use of Distinct and LIKE, Update records)
  3. Dealing with Null/Empty values (convert empty to null values, Inner Joins to populate null values)
  4. Remove columns/rows (Alter... Drop, Delete records)

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Data cleaning process in SQL on a global dataset of company layoffs to ensure accuracy and consistency for analysis

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