Snapbizz FMCG Transaction Data for AI&ML Training - POS Data India
# | Store_ID |
Store_Name |
Metro_City |
Invoice_ID |
Bill_date |
Date |
Month |
Week |
Hour |
Barcode |
Local_Item_Code |
Item_Description |
Centralized_Description |
Brand |
Manufacturer_Name |
Category |
Sub_Category |
Quantity |
Selling_Price |
Total_Amount |
MRP |
Bill_Amount |
Loose_Item_Flag |
is_credit |
Pincode |
Zone |
Market_Cap |
Payment_Mode |
Payment_Type |
|
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
1 | xxxxxxxxxx | Xxxxxxxxx | xxxxxx | xxxxxxxxxx | Xxxxx | Xxxxxx | Xxxxxxxxxx | Xxxxxx | Xxxxxxxxx | Xxxxxxxxxx | xxxxxxxxx | Xxxxxxxxx | xxxxxxxxx | Xxxxxxx | xxxxxx | Xxxxx | xxxxxxxxxx | xxxxxx | Xxxxxxxxxx | xxxxxx | Xxxxx | Xxxxxx | xxxxx | xxxxxxxx | xxxxxxx | Xxxxx | Xxxxxxxx | xxxxxxxxxx | xxxxxx | Xxxxxxxxx |
2 | xxxxxx | Xxxxxxxxx | Xxxxxxxxx | xxxxxxxxxx | Xxxxxx | Xxxxx | xxxxxx | xxxxxxx | xxxxxxx | Xxxxx | xxxxxx | Xxxxxxxxxx | xxxxxxxx | xxxxxx | Xxxxx | Xxxxxxx | xxxxxx | Xxxxxxxx | Xxxxxxx | Xxxxx | xxxxxx | xxxxxxxxxx | Xxxxx | xxxxxxxxxx | xxxxxxxxx | Xxxxxxx | xxxxxxxx | xxxxxxxx | Xxxxxxxxxx | Xxxxxxxx |
3 | Xxxxxxxx | xxxxxxxxx | Xxxxxxxxxx | Xxxxxx | Xxxxxxxxx | xxxxx | xxxxxxx | xxxxxxxxx | Xxxxxx | Xxxxxxx | Xxxxxxxxx | xxxxxxxxx | xxxxxxxxx | Xxxxx | xxxxxxxx | Xxxxxxx | xxxxxxxxx | Xxxxxxx | xxxxx | Xxxxxxx | xxxxxxx | Xxxxx | xxxxxxxxxx | Xxxxxxx | Xxxxx | xxxxxxxxxx | Xxxxxx | xxxxxx | Xxxxxxxxx | xxxxx |
4 | Xxxxxxxxxx | xxxxxx | xxxxx | xxxxxxxx | Xxxxxx | Xxxxxxxxxx | xxxxxxxxx | Xxxxxxxxxx | xxxxxxxx | xxxxx | Xxxxxx | xxxxxxxxxx | xxxxxxxxx | xxxxx | xxxxx | xxxxxxxx | xxxxxx | Xxxxxxxxxx | xxxxxxxxxx | Xxxxx | xxxxxxx | Xxxxxxxx | Xxxxxxx | xxxxx | xxxxxxxx | xxxxxxxxxx | Xxxxxx | xxxxxxxxx | Xxxxx | xxxxx |
5 | xxxxxxxxx | xxxxxxx | Xxxxxxxxx | Xxxxxxx | xxxxxxxxxx | Xxxxx | xxxxxxxxx | xxxxxxx | Xxxxxx | xxxxxxxxx | xxxxx | Xxxxxxx | xxxxxxxxx | Xxxxxxxx | xxxxxxxx | Xxxxxxxx | Xxxxxxxx | xxxxxxxx | xxxxxxxxx | Xxxxxxx | Xxxxxxxxx | xxxxxxxx | xxxxx | Xxxxxxxxxx | xxxxxxxxxx | xxxxxx | Xxxxx | Xxxxxxx | Xxxxx | Xxxxxx |
6 | Xxxxx | Xxxxxxxxx | xxxxxx | xxxxxxxx | Xxxxxxxxx | Xxxxxx | Xxxxxxxxxx | Xxxxxx | Xxxxx | Xxxxxxx | xxxxxxxxx | Xxxxx | xxxxx | Xxxxxx | xxxxxxxxx | xxxxxxx | xxxxxxxxx | Xxxxxxxxxx | xxxxxxxxx | Xxxxx | Xxxxx | Xxxxxxxxx | xxxxxxxxxx | xxxxxx | xxxxxxxxx | xxxxxxx | Xxxxxxx | Xxxxxxxxxx | Xxxxxxxxxx | Xxxxxxxx |
7 | Xxxxxxxxx | xxxxx | Xxxxxxx | xxxxxxxxxx | Xxxxxxxxx | Xxxxxxxx | xxxxxxxxxx | xxxxxxx | Xxxxxxxx | xxxxx | Xxxxxx | xxxxxx | xxxxxxxx | xxxxxxx | Xxxxx | Xxxxxxxxx | Xxxxx | Xxxxxxx | Xxxxxxxx | xxxxxxxxx | xxxxxxxx | xxxxx | Xxxxxxxxxx | Xxxxxxx | xxxxxxxxx | xxxxxxx | xxxxxxxxxx | xxxxxx | xxxxx | Xxxxxxxxxx |
8 | Xxxxxxxxx | xxxxxxx | Xxxxxx | Xxxxx | Xxxxxxxx | xxxxxxxxx | xxxxxxxx | Xxxxxx | xxxxxxxxxx | xxxxxxxxx | xxxxx | Xxxxx | xxxxxxx | xxxxxxxxxx | Xxxxxx | Xxxxxxxxx | xxxxxxx | Xxxxxxxx | xxxxx | xxxxx | Xxxxxxxxxx | Xxxxxxx | Xxxxxxxx | Xxxxxxx | xxxxx | xxxxxxx | Xxxxx | xxxxxxxxxx | Xxxxxxxxxx | xxxxxxx |
9 | Xxxxx | xxxxxxxxx | xxxxxxxx | Xxxxxxxx | xxxxxxxx | Xxxxxxx | Xxxxxx | Xxxxxxxxx | Xxxxxxxx | Xxxxxxxxxx | Xxxxxxx | Xxxxxx | Xxxxxxxxxx | xxxxxxxxxx | xxxxxxxxxx | Xxxxxxx | Xxxxx | Xxxxx | Xxxxx | Xxxxxxx | xxxxx | xxxxxxxxx | xxxxxxx | Xxxxxxx | xxxxxx | xxxxxxxxxx | xxxxxxxxxx | Xxxxxxx | xxxxxxxxx | Xxxxx |
10 | xxxxxxx | Xxxxxx | Xxxxx | xxxxxxxxxx | xxxxxxxxx | Xxxxxxxxxx | Xxxxxxxxx | Xxxxxxxx | xxxxxxxxx | Xxxxxxx | Xxxxxxx | Xxxxx | xxxxxxxxxx | Xxxxxxxxx | Xxxxxxx | Xxxxxxx | xxxxxxxx | xxxxx | Xxxxx | Xxxxxxxx | xxxxxxxx | Xxxxxxxxx | xxxxxxxxxx | xxxxxxxxxx | xxxxxxxxx | xxxxxxxxx | Xxxxxxx | Xxxxxxx | Xxxxxxx | Xxxxxxx |
... | xxxxxxx | Xxxxxxxxxx | xxxxxxxx | Xxxxx | xxxxxxxxxx | xxxxxxxxxx | xxxxxx | xxxxxxxx | Xxxxxxxx | xxxxxx | xxxxxxxx | xxxxxx | Xxxxxxxx | xxxxxxxxx | xxxxx | Xxxxxxxxxx | Xxxxxxxxx | Xxxxxxx | xxxxxxxx | Xxxxxxx | Xxxxxxxxxx | Xxxxxxxxx | xxxxxxxxxx | xxxxxxx | Xxxxxxxxx | xxxxxxxxx | xxxxxxxx | xxxxxxxxx | xxxxx | Xxxxx |
Data Dictionary
Attribute | Type | Example | Mapping |
---|---|---|---|
Store_ID
|
Integer | 11613 | |
Store_Name
|
String | GANESH STORE BW | |
Metro_City
|
String | Mumbai | |
Invoice_ID
|
String | 11613-1118013392 | |
Bill_date
|
String | 02/01/2019 11:47:45 AM | |
Date
|
String | 01/02/2019 | |
Month
|
String | 19-Feb | |
Week
|
String | W4 | |
Hour
|
Integer | 11 | |
Barcode
|
Integer | 8901491503051 | |
Local_Item_Code
|
|||
Item_Description
|
String | LAYS HOT SWEET CHILLI POTATO CHIPS 25 GM PLS | |
Centralized_Description
|
String | LAYS CARIBBEAN HOT & SWEET CHILLI 26 GMS | |
Brand
|
String | LAYS | |
Manufacturer_Name
|
String | PEPSICO INDIA | |
Category
|
String | SNACK FOODS | |
Sub_Category
|
String | NA | |
Quantity
|
Integer | 1 | |
Selling_Price
|
Integer | 10 | |
Total_Amount
|
Integer | 10 | |
MRP
|
Integer | 10 | |
Bill_Amount
|
Integer | 10 | |
Loose_Item_Flag
|
Boolean | f | |
is_credit
|
Boolean | t | |
Pincode
|
Integer | 400074 | |
String | Maharashtra | State Name | |
Zone
|
String | West | |
Market_Cap
|
String | Mumbai | |
Payment_Mode
|
String | CASH | |
Payment_Type
|
String | CREDIT |
Attribute | Type | Example | Mapping |
---|---|---|---|
Invoice ID
|
10263-2019008096 | ||
Item Descriptiom
|
Atta | ||
Centralized Description
|
Aashirvaad Shudh Chakki Atta 5 Kg | ||
Total Amount
|
500 |
Description
Country Coverage
History
Volume
500 million | records |
Pricing
Suitable Company Sizes
Quality
Delivery
Use Cases
Categories
Related Searches
Related Products
Frequently asked questions
What is Snapbizz FMCG Transaction Data for AI&ML Training - POS Data India?
it’s the blueprint of consumer behavior, meticulously “Collected From POS Transactions”. This dynamic dataset encapsulates every facet of product transactions - prices, quantities, discounts, and beyond.,.
What is Snapbizz FMCG Transaction Data for AI&ML Training - POS Data India used for?
This product has 5 key use cases. Snapbizz recommends using the data for Artificial Intelligence (AI), Machine Learning (ML), consumer spending data, AI training data, and ml training data. Global businesses and organizations buy Consumer Behavior Data from Snapbizz to fuel their analytics and enrichment.
Who can use Snapbizz FMCG Transaction Data for AI&ML Training - POS Data India?
This product is best suited if you’re a Small Business, Medium-sized Business, or Enterprise looking for Consumer Behavior Data. Get in touch with Snapbizz to see what their data can do for your business and find out which integrations they provide.
How far back does the data in Snapbizz FMCG Transaction Data for AI&ML Training - POS Data India go?
This product has 5 years of historical coverage. It can be delivered on a monthly, quarterly, yearly, and on-demand basis.
Which countries does Snapbizz FMCG Transaction Data for AI&ML Training - POS Data India cover?
This product includes data covering 1 country like India. Snapbizz is headquartered in India.
How much does Snapbizz FMCG Transaction Data for AI&ML Training - POS Data India cost?
Pricing information for Snapbizz FMCG Transaction Data for AI&ML Training - POS Data India is available by getting in contact with Snapbizz. Connect with Snapbizz to get a quote and arrange custom pricing models based on your data requirements.
How can I get Snapbizz FMCG Transaction Data for AI&ML Training - POS Data India?
Businesses can buy Consumer Behavior Data from Snapbizz and get the data via S3 Bucket and Email. Depending on your data requirements and subscription budget, Snapbizz can deliver this product in .csv format.
What is the data quality of Snapbizz FMCG Transaction Data for AI&ML Training - POS Data India?
Snapbizz has reported that this product has the following quality and accuracy assurances: 100% real time data. You can compare and assess the data quality of Snapbizz using Datarade’s data marketplace.
What are similar products to Snapbizz FMCG Transaction Data for AI&ML Training - POS Data India?
This product has 3 related products. These alternatives include Snapbizz FMCG Financial Data POS Transaction Data, Factori AI & ML Training Data Consumer Data USA Machine Learning Data, and Consumer Edge Vision Consumer Transaction Data USA Data 100M+ Credit & Debit Cards, 12K+ Merchants, 800+ Parent Companies, 600+ Tickers. You can compare the best Consumer Behavior Data providers and products via Datarade’s data marketplace and get the right data for your use case.