This project is based on imaginary Analysing Zomato Dataset I found on kaggle. It's a perfect dataset to explore and understand Analysis and operational efficiency.
- Explore and analyze Zomato data to make understand Analysis and operational efficiency.
- Address questions about Dataset.
- The dataset was obtained from Kaggle and is publicly accessible.
- Minimal preprocessing was performed, focusing on Country code adjustments for compatibility. The data was not fully clean. I was performed preprocessing for analysis.
- All dataset files are included within the project repository.
It contains 2 sheets/tables:
- zomato_World_dataset.csv
- Country-Code.xlsx
Python for data analysis and applied essential concepts like data transformation and visualization.
Utilzed Python libraries such as:
- Pandas
- Numpy
- Matplotlib
- Seaborn
- Data Preprocessing
- Data Manipulation
- Data Visualization
- Data Cleaning
- Statistical Analysis
- Problem Solving
- Communication
The Zomato Analysis Report suggests that the company is well-positioned for continued success, driven by a combination of strategic foresight, technological prowess, and a customer-centric approach. As the food delivery landscape continues to evolve, Zomato's ability to navigate challenges and capitalize on opportunities will play a pivotal role in shaping its future trajectory.
Overall, the analysis underscores the resilience of Zomato as a major player in the evolving food delivery ecosystem. As the company navigates through the ever-changing landscape, adapting to emerging trends and maintaining a focus on customer satisfaction will be pivotal for its long-term success. Investors, stakeholders, and the company itself can use these findings as a foundation for informed decision-making and strategic planning in the dynamic and competitive food delivery market.
Alok Choudhary (Data Scientist)
LinkedIn Profile: Alok Choudhary
