Data Cleaning and EDA project
Tech companies worldwide are grappling with an economic slowdown, driven by reduced consumer spending, rising interest rates from central banks, and a strong U.S. dollar. These factors are signaling a potential recession, prompting many firms to begin layoffs. Meta, for instance, recently laid off 13% of its workforce—more than 11,000 employees—as a direct response to these challenges. To build a workflow:
- Stored the raw data on premise easy access.
- Cleaned and transformed the data using PostgreSQL, fixing missing values, standardizing fields, and ensuring the data was analysis-ready.
Steps involved in cleaning a messy dataset:
- Removing Duplicates
- Standardizing Data
- Null/Blank Values
- Remove Unnecessary Columns/Rows
Key Findings:
- The U.S. saw the highest number of layoffs, with India and Germany close behind—highlighting how widespread the impact has been.
- Even AI-focused companies took a hit, signaling both a market correction and changing industry priorities.
- Big funding didn’t mean job security—some of the most well-backed companies faced the deepest cuts.
I'm currently working on a PowerBI dashboard that will help visualize the data
Coming soon:
- Store data in Amazon S3 bucket for scalability
- Use Snowflake to transform data
- Use PowerBI to buld an interactive dashboard
Get In Touch!
