In this project I used public API keys and Python web scraping for getting the data.
Then I used Bash for data cleaning, SQL for exploratory data analysis
and Power BI for visualizing my key insights.
Analyzed the Maven Analytics' restaurant orders dataset using PostgreSQL, revealing insights and enhancing visuals with Snappify.
Focused on the analysis of rental properties in Budapest leveraging Python for web scraping and data cleaning, along with Excel for visualization.
Analyzed a fictional travel blog business using SQL for data manipulation, Python for additional scripting, and Looker Studio for comprehensive data visualization.
Analyzed a 1000-row coffee sales dataset using functions, charts, and pivot tables in Excel to derive insights and trends, facilitating informed decision-making.