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Sports clothing is a booming sector! In this notebook, you will use your SQL skills to analyze product data for an online sports retail company. You will work with numeric, string, and timestamp data on pricing and revenue, ratings, reviews, descriptions, and website traffic. You will use techniques such as aggregation, cleaning, labeling, Common Table Expressions, and correlation to produce recommendations on how the company can maximize revenue!
- 1Counting missing values
- 2Nike vs Adidas pricing
- 3Labeling price ranges
- 4Average discount by brand
- 5Correlation between revenue and reviews
- 6Ratings and reviews by product description length
- 7Reviews by month and brand
- 8Footwear product performance
- 9Clothing product performance
Core Curriculum Manager, DataCamp
George is a Core Curriculum Manager at DataCamp. He has experience in project management across public health, applied research, and not-for-profit sectors. George is passionate about health technologies and all things data science.
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