Product Dataset Structure1234567890-.pptx

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1. Product Dataset Structure E-commerce Product Information

2. Introduction In today's data-driven market, having a robust and comprehensive product dataset is crucial for the success of any e-commerce business. This presentation outlines the essential features and columns that should be included to ensure data accuracy, completeness, and usefulness.

3. Available Columns Data that can be added Every product entry must contain fundamental identifiers and classifications to facilitate easy cataloging and searching. Bar-Code No. Logic Description Print Description Description 2 Search Description Base Unit of Measure Attribute Val Code 1 COLLECTION CODE Attribute Val Code 2 ARTICLE CODE FABRIC QUALITY CODE Attribute Val Code 4 Attribute Val Code 5 COLOR CODE Attribute Val Code 6 SIZE Attribute Val Code 7 PARCK OF CODE Attribute Val Code 8 Gender Attribute Val Code 9 BLEND SEASON Unit Cost MRP Price GST _ HSN_SAC Code ( eg - 95030090) Logic Description company name Order Quantity Vendor Grand Parent

4. Currently Selected 1. Barcode No. 2. Fabric 3. Product 4. Color 5. Gender 6. Blend (not confirmed yet) 7. Category 8. Season 10. Vendor 11. MRP

5. Gender 1. Ideas about which products are for unisex, boy, girl. Time required – 15-20 minutes

6. Blend What to put in blend currently.

7. Vendor Name Detailed descriptions of vendor name or vendor code Vendor name can be Vendor name Empty Vendor code

8. MRP MRP Column is to be build Pricing can be fixed of every 106 product. It can be filled with fake data. It can be empty.

9. Conclusion A well-structured product dataset is the backbone of our e-commerce operations. By incorporating these essential features, we can enhance our data quality, streamline processes, and ultimately improve customer satisfaction.