This case study focuses on Swiggy, a leading food delivery service, and its dataset comprising information about restaurants and their offers in the Mumbai location. The objective of this case study is to clean and manipulate the dataset using MySQL to derive meaningful insights. The dataset includes detailed records of restaurants, their offers, and other relevant attributes. By performing data cleaning and manipulation tasks in MySQL, we aim to transform the raw data into a structured format suitable for analysis.
The primary objective of this case study is to utilize MySQL for data cleaning and manipulation of the Swiggy dataset related to restaurants and their offers in Mumbai. The goal is to ensure data integrity, remove inconsistencies, and perform necessary transformations to prepare the data for analysis. Following the data preparation, we will analyze the dataset to extract top 10 insights that can provide valuable information for decision-making. These insights will be documented in a comprehensive report.
The analysis of Swiggy's Mumbai restaurant offers dataset using MySQL has yielded significant insights through meticulous data cleaning and manipulation. The process involved standardizing the data, addressing missing values, and transforming the dataset into a coherent structure for analysis.
Here are the top 10 insights derived from the analysis:
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Distinct Food Items in Kandivali East: Listed all unique food items available in Kandivali East.
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Average Rating for Hotels in Kandivali East: Calculated the average rating for each hotel in Kandivali East.
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Offers up to 80: Identified food items with offers up to a value of 80.
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Shortest Delivery Time in Kandivali West: Found hotels with the shortest delivery times in Kandivali West.
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Hotels in Borivali: Listed hotels with a count of items offered and an average rating greater than 4 in Borivali.
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Higher Average Offer Percentage in Kandivali East: Identified hotels with higher average offer percentages in Kandivali East.
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Comparison between McDonald's and KFC in Kandivali East: Compared the average delivery time and rating between McDonald's and KFC in Kandivali East.
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Best Offer for Burger: Listed the best offer for burgers along with hotel names and locations.
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Correlation Coefficient: Derived the correlation coefficient for relevant variables.
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Top 5 Hotels in Kandivali East: Identified the top 5 hotels with the best offers and shortest delivery times in Kandivali East.
These insights provide a comprehensive understanding of the restaurant landscape in Mumbai as seen through Swiggy's platform. They offer actionable intelligence for restaurant owners to tailor their offerings, for Swiggy to optimize their platform, and for customers to make informed dining choices.
The structured approach to data cleaning and manipulation in MySQL has ensured the accuracy and reliability of the findings. This case study demonstrates the power of database management and analysis in deriving meaningful insights from complex datasets, ultimately contributing to better decision-making in the competitive food delivery market.