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https://github.com/niteshchawla/nc-sql-business-case
A Leading Retail chain brand and a prominent retailer in the United States. It makes itself a preferred shopping destination by offering outstanding value, inspiration, innovation and an exceptional guest experience that no other retailer can deliver.
https://github.com/niteshchawla/nc-sql-business-case
bigquery retail sql supermarket
Last synced: 17 days ago
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A Leading Retail chain brand and a prominent retailer in the United States. It makes itself a preferred shopping destination by offering outstanding value, inspiration, innovation and an exceptional guest experience that no other retailer can deliver.
- Host: GitHub
- URL: https://github.com/niteshchawla/nc-sql-business-case
- Owner: Niteshchawla
- Created: 2024-06-26T12:14:53.000Z (8 months ago)
- Default Branch: main
- Last Pushed: 2024-06-26T12:25:33.000Z (8 months ago)
- Last Synced: 2025-01-21T22:09:56.221Z (17 days ago)
- Topics: bigquery, retail, sql, supermarket
- Homepage:
- Size: 396 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# NC-SQL-Business-Case
A Leading Retail chain brand and a prominent retailer in the United States. It makes itself a preferred shopping destination by offering outstanding value, inspiration, innovation and an exceptional guest experience that no other retailer can deliver.
This particular business case focuses on the operations of Target in Brazil and provides insightful information about 100,000 orders placed between 2016 and 2018. The dataset offers a comprehensive view of various dimensions including the order status, price, payment and freight performance, customer location, product attributes, and customer reviews.
By analyzing this extensive dataset, it becomes possible to gain valuable insights into it's operations in Brazil. The information can shed light on various aspects of the business, such as order processing, pricing strategies, payment and shipping efficiency, customer demographics, product characteristics, and customer satisfaction levels.