The approach to analyzing the Yelp data involves several key steps: preprocessing the dataset, using various analysis methods (regression, classification, clustering, time series analysis), evaluating the data from different perspectives (platform, users, merchants), creating visual representations Time series analysis is particularly important, focusing on user reviews and merchant feedback over time to identify trends and changes. Tools like Python, R, and SQL are used for scripting, statistical analysis, and data querying. The project aims to provide deep insights into user behaviors and business operations on Yelp, underlining the importance of analytical skills, problem-solving abilities, and teamwork in data analysis projects
- Python, R, SQL
- Time Series Analysis
- Regression Analysis
- Data Preprocessing
- Data Visualization