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Optimizing Online Sports Retail Revenue

Analyze product data for an online sports retail company to optimize revenue.

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9 Tasks1,500 XP

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Project Description

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!

Project Tasks

  1. 1
    Counting missing values
  2. 2
    Nike vs Adidas pricing
  3. 3
    Labeling price ranges
  4. 4
    Average discount by brand
  5. 5
    Correlation between revenue and reviews
  6. 6
    Ratings and reviews by product description length
  7. 7
    Reviews by month and brand
  8. 8
    Footwear product performance
  9. 9
    Clothing product performance




Data Manipulation
George Boorman HeadshotGeorge Boorman

Curriculum Manager, DataCamp

George is a Curriculum Manager at DataCamp. He holds a PGDip in Exercise for Health and BSc (Hons) in Sports Science and has experience in project management across public health, applied research, and not-for-profit sectors. George is passionate about sports, tech for good, and all things data science.
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