Zomato, founded in 2008, is an Indian company that provides information, menus, and user-reviews of a wide range of restaurants, and also has food delivery options from partner restaurants in select cities.
DATASET AND TOOLS
The dataset used for this project was found on an online public data platform called Kaggle. It was relatively clean and did not require any major changes. Open refine was used to make a few alterations. For instance, country codes were switched to country names to avoid any confusion and for better understandability.
Once the dataset was refined, Tableau public was used to create interactive charts and graphs.
As Zomato is an Indian company, I decided to focus on restaurants in India and its cities. The first sheet I created focused on the number of restaurants that have partnered with Zomato in different cities. A horizontal bar chart was used for the representation.
The next sheet uses a treemap to represent different cuisines based on people’s preferences.
Further, I created 2 pie charts to show online delivery and table booking options in restaurants and an overall rating highlight table. As there were only 2 sections (yes/no), the pie chart was a good tool to depict the results.
To create a cohesive visual language, all the charts and graphs shared the same color palette. The sheets were then complied into a single dashboard. I wanted the visualization to be interactive and hence added a city-specific filter.
- New Delhi has the maximum number of restaurants that have partnered with Zomato.
- North Indian cuisine is the most preferred and searched for.
This project helped me understand and study data better. Tableau public is fun and easy to learn. There were a few changes that I could directly make in the dataset using Tableau. By simply dragging and dropping data, I created 17 charts and graphs in a couple of hours and eventually picked 5 of them for the final dashboard.
The selected dataset didn’t require a lot of cleaning up but I would have liked to manipulate it more to try and produce different stories. The visualization focuses on very broad categories right now. I would like to add to this project by adding individual restaurants for each city with their ratings and add filters like cuisines and cost. Although ratings are important, I thought to put cumulative ratings for all the restaurants was slightly vague. I would also have liked to experiment with the maps as Zomato is present in a lot of different countries and regions.