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Zomato Application Data Analytics πŸ½οΈπŸ“Š

INTRODUCTION

Zomato is a global leader in food delivery and restaurant discovery services, operating in various countries. Leveraging data analytics provides valuable insights to drive strategic decisions, enhance customer experiences, and optimize service offerings. This project focuses on applying data analysis techniques to Zomato's vast resources to improve its overall business strategy.

PROJECT OVERVIEW

The project will be executed in three phases:

  • Data Collection and Preparation: Extract data from the Zomato API or internal databases, clean it to address inconsistencies, and transform it into a structured format for analysis.

  • Exploratory Data Analysis (EDA): Explore the prepared data to uncover meaningful patterns and trends through summary statistics, visualizations, and statistical techniques.

  • Actionable Recommendations: Develop strategic recommendations based on insights gained, focusing on optimizing areas like top-performing restaurants, ideal locations, customer satisfaction, delivery options, and popular cuisines.

DATASETS

The following datasets will be utilized in this project:

  • Restaurant Details: Information about restaurants, including name, location, cuisine, and ratings.
  • Customer Reviews: User-generated reviews and ratings for various restaurants.
  • Order Data: Details on customer orders, including items ordered, prices, and timestamps.
  • Delivery Times: Data on delivery times for different restaurants and orders.

TOOLS & LIBRARIES

The following libraries will be utilized for analysis:

  • NumPy: Numerical computations and data manipulation.
  • Pandas: Data manipulation and handling structured datasets.
  • Matplotlib & Seaborn: Data visualization for clear insights.

ENVIRONMENT

The analysis will be conducted in Jupyter Notebook, a web-based environment for interactive computing. Jupyter supports Python 3.x and can be installed via pip. Launch the notebook by navigating to the desired directory and running:

jupyter notebook

This will start a local server at localhost:8888 for interactive analysis.

CONCLUSION

Zomato has access to a wealth of data, including customer reviews, restaurant details, and order information. Analyzing this data enables Zomato to identify trends, optimize operations, and improve customer engagement. By leveraging data analytics, Zomato can gain insights into customer preferences, evaluate restaurant performance, and tailor its services to meet user demands.

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πŸ“Š Exploratory Data Analysis on Zomato app data to uncover trends, insights, and user behavior.

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