Data Analysis involves creating a compelling narrative using data for effective communication. It often utilizes visualization methods like plots, charts, and tables to convey insights beyond formal modeling or hypothesis testing tasks.
Domain: Marketing
Refer to the provided data dictionary in an Excel file for additional information.
A restaurant consolidator seeks to enhance its B-to-C portal using intelligent automation technology. It aims to identify and recommend restaurants using different metrics. Understanding the behavior of the available data is crucial for building an effective model.
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Data Preliminary Analysis:
- Perform preliminary data inspection to understand its structure, identify missing values, duplicates, etc.
- Explore the geographical distribution of restaurants and ratings.
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Project Tasks:
- Import, understand, and inspect the data.
- Explore franchise presence, table booking, online delivery, votes distribution, top cuisines, etc.
- Analyze the relationship between factors like number of cuisines, cost, delivery option, and ratings.
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Data Inspection:
- Identify structure, missing values, duplicates, etc.
- Remove duplicates based on findings.
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Exploration:
- Analyze geographical distribution of restaurants.
- Explore franchise presence.
- Investigate table booking and online delivery ratios.
- Compare votes for restaurants with and without delivery options.
- Exploratory Data Analysis (EDA) & Dashboarding:
- Determine top 10 cuisines across cities.
- Analyze cuisine diversity per restaurant and across cities.
- Examine cost distribution and its impact on ratings.
- Visualize factors affecting ratings using Tableau.
- Preliminary data analysis report.
- Insights on franchise presence, table booking, online delivery, etc.
- Visualization of top cuisines, cost distribution, and factors affecting ratings.
- Recommendations for improving the B-to-C portal based on findings.