MySQL Data Cleaning Project

Purpose of Project

• Clean and prepare the dataset for the Exploratory Data Process.

Context

Tech firms around the globe are fighting the economic slowdown. The slow consumer spending, higher interest rates by central banks, and strong dollars overseas are hinting toward a possible recession, and tech firms have started laying employees off. This economic slowdown has made Meta recently fire 13% of its workforce, which amounts to more than 11,000 employees. This dataset was made with the hope of enabling the Kaggle community to look into analyzing recent tech turmoil and discover useful insights.

Part 1

Import data and start to clean by

• 1. Check for duplicates and remove any
• 2. Standardize data and fix errors
• 3. Look at null values and see what
• 4. Remove any columns and rows that are not necessary

Part 2

Explore the data to identify patterns

• When did these layoffs occur?
• What industry has had the most layoffs?
• Dates of layoffs (is there a particular pattern for the timing of layoffs?)
• What industry is least affected by layoffs?
• How does this vary by country?
• Does funding influence if layoffs increase or decrease?

Reference

Data Source for the project can be found here: https://www.kaggle.com/datasets/swaptr/layoffs-2022