🎯 About This Dataset
This is the messy e-commerce data used in Day 12 SQL Challenge. Download these CSV files, import into your SQL database, and practice your data cleaning skills!
📋 Table 1: raw_transactions
| trans_id | customer_email | product_sku | amount | trans_date | status |
|---|---|---|---|---|---|
| TX001 | JOHN@EMAIL.COM | SKU-123-A | $125.50 | 2024-01-15 14:30:00 | completed |
| TX002 | sarah.j@invalid | sku-456-b | 45 | 15/01/2024 | PENDING |
| TX003 | mike@shop.com | SKU-789-C | $0 | 2024-01-20 | Cancelled |
| TX004 | emma@store.io | sku-123-a | 125.50 | 2024/01/25 10:15 | COMPLETED |
| TX005 | LISA@EMAIL.COM | SKU-999 | NULL | 2024-02-01 | failed |
| TX006 | bob_jones | SKU-456-B | $45.00 | 01-02-2024 | completed |
| TX007 | anna@site.com | sku-789-c | 299.99 | 2024-02-10 16:45:30 | Completed |
| TX008 | DAVID@MAIL.NET | SKU-123-A | $-50 | 2024-02-15 | refund |
| TX009 | grace@email.com | sku-999 | 750.00 | 2024-02-20T14:30 | COMPLETED |
| TX010 | henry@shop.com | SKU-456-b | $45.0 | 2024/02/25 | pending |
📦 Table 2: product_catalog
| sku | product_name | category | price |
|---|---|---|---|
| SKU-123-A | Wireless Mouse | Electronics | 125.50 |
| SKU-456-B | USB Cable | Accessories | 45.00 |
| SKU-789-C | Laptop Stand | Furniture | 299.99 |
| SKU-999 | Premium Headset | Electronics | 750.00 |
👥 Table 3: customer_profiles
| full_name | join_date | country | |
|---|---|---|---|
| john@email.com | john smith | 2023-05-10 | USA |
| SARAH.J@INVALID | Sarah Jones | 05/10/2023 | uk |
| mike@shop.com | MIKE WILSON | 2023-06-15 | Canada |
| emma@store.io | Emma Brown | 2023/07/20 | USA |
| LISA@EMAIL.COM | lisa garcia | 20-08-2023 | spain |
| anna@site.com | Anna Martinez | 2023-09-01 | MEXICO |
| DAVID@MAIL.NET | david LEE | 10/09/2023 | usa |
| grace@email.com | Grace Taylor | 2023-10-15 | UK |
| henry@shop.com | HENRY ZHANG | 2023/11/20 | canada |
💡 How to Use This Data
Step 1: Download all 3 CSV files using the buttons above
Step 2: Import them into your SQL database (MySQL, PostgreSQL, SQL Server, etc.)
Step 3: Practice the Day 12 data cleaning challenge!
Step 4: Share your solution on LinkedIn with #100DaysSQLChallenge