
Large Language Model (LLM) Data | Machine Learning (ML) Data | AI Training Data (RAG) for 1M+ Global Grocery, Restaurant, and Retail Stores
# | lineage |
image |
price |
store_name |
local_hours |
pickup_enabled |
delivery_enabled |
store_type |
updated |
street_addr |
city |
state |
zipcode |
country |
lon |
|||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
1 | xxxxxxxxxx | Xxxxxxxxx | xxxxxx | xxxxxxxxxx | Xxxxx | Xxxxxx | Xxxxxxxxxx | Xxxxxx | Xxxxxxxxx | Xxxxxxxxxx | xxxxxxxxx | Xxxxxxxxx | xxxxxxxxx | Xxxxxxx | xxxxxx | Xxxxx | xxxxxxxxxx | xxxxxx | Xxxxxxxxxx | xxxxxx |
2 | Xxxxx | Xxxxxx | xxxxx | xxxxxxxx | xxxxxxx | Xxxxx | Xxxxxxxx | xxxxxxxxxx | xxxxxx | Xxxxxxxxx | xxxxxx | Xxxxxxxxx | Xxxxxxxxx | xxxxxxxxxx | Xxxxxx | Xxxxx | xxxxxx | xxxxxxx | xxxxxxx | Xxxxx |
3 | xxxxxx | Xxxxxxxxxx | xxxxxxxx | xxxxxx | Xxxxx | Xxxxxxx | xxxxxx | Xxxxxxxx | Xxxxxxx | Xxxxx | xxxxxx | xxxxxxxxxx | Xxxxx | xxxxxxxxxx | xxxxxxxxx | Xxxxxxx | xxxxxxxx | xxxxxxxx | Xxxxxxxxxx | Xxxxxxxx |
4 | Xxxxxxxx | xxxxxxxxx | Xxxxxxxxxx | Xxxxxx | Xxxxxxxxx | xxxxx | xxxxxxx | xxxxxxxxx | Xxxxxx | Xxxxxxx | Xxxxxxxxx | xxxxxxxxx | xxxxxxxxx | Xxxxx | xxxxxxxx | Xxxxxxx | xxxxxxxxx | Xxxxxxx | xxxxx | Xxxxxxx |
5 | xxxxxxx | Xxxxx | xxxxxxxxxx | Xxxxxxx | Xxxxx | xxxxxxxxxx | Xxxxxx | xxxxxx | Xxxxxxxxx | xxxxx | Xxxxxxxxxx | xxxxxx | xxxxx | xxxxxxxx | Xxxxxx | Xxxxxxxxxx | xxxxxxxxx | Xxxxxxxxxx | xxxxxxxx | xxxxx |
6 | Xxxxxx | xxxxxxxxxx | xxxxxxxxx | xxxxx | xxxxx | xxxxxxxx | xxxxxx | Xxxxxxxxxx | xxxxxxxxxx | Xxxxx | xxxxxxx | Xxxxxxxx | Xxxxxxx | xxxxx | xxxxxxxx | xxxxxxxxxx | Xxxxxx | xxxxxxxxx | Xxxxx | xxxxx |
7 | xxxxxxxxx | xxxxxxx | Xxxxxxxxx | Xxxxxxx | xxxxxxxxxx | Xxxxx | xxxxxxxxx | xxxxxxx | Xxxxxx | xxxxxxxxx | xxxxx | Xxxxxxx | xxxxxxxxx | Xxxxxxxx | xxxxxxxx | Xxxxxxxx | Xxxxxxxx | xxxxxxxx | xxxxxxxxx | Xxxxxxx |
8 | Xxxxxxxxx | xxxxxxxx | xxxxx | Xxxxxxxxxx | xxxxxxxxxx | xxxxxx | Xxxxx | Xxxxxxx | Xxxxx | Xxxxxx | Xxxxx | Xxxxxxxxx | xxxxxx | xxxxxxxx | Xxxxxxxxx | Xxxxxx | Xxxxxxxxxx | Xxxxxx | Xxxxx | Xxxxxxx |
9 | xxxxxxxxx | Xxxxx | xxxxx | Xxxxxx | xxxxxxxxx | xxxxxxx | xxxxxxxxx | Xxxxxxxxxx | xxxxxxxxx | Xxxxx | Xxxxx | Xxxxxxxxx | xxxxxxxxxx | xxxxxx | xxxxxxxxx | xxxxxxx | Xxxxxxx | Xxxxxxxxxx | Xxxxxxxxxx | Xxxxxxxx |
10 | 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 | Xxxxxxxxx | xxxxxxx | Xxxxxx | Xxxxx | Xxxxxxxx | xxxxxxxxx | xxxxxxxx | Xxxxxx | xxxxxxxxxx | xxxxxxxxx |
# | store_uuid |
store_type |
unit_size |
unit_measurement |
delivery_enabled |
pickup_enabled |
price |
full_price |
product_image |
lineage |
updated |
street_addr |
country |
lon |
|||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
1 | xxxxxxxxxx | Xxxxxxxxx | xxxxxx | xxxxxxxxxx | Xxxxx | Xxxxxx | Xxxxxxxxxx | Xxxxxx | Xxxxxxxxx | Xxxxxxxxxx | xxxxxxxxx | Xxxxxxxxx | xxxxxxxxx | Xxxxxxx | xxxxxx | Xxxxx | xxxxxxxxxx | xxxxxx | Xxxxxxxxxx | xxxxxx | Xxxxx | Xxxxxx | xxxxx |
2 | xxxxxxxx | xxxxxxx | Xxxxx | Xxxxxxxx | xxxxxxxxxx | xxxxxx | Xxxxxxxxx | xxxxxx | Xxxxxxxxx | Xxxxxxxxx | xxxxxxxxxx | Xxxxxx | Xxxxx | xxxxxx | xxxxxxx | xxxxxxx | Xxxxx | xxxxxx | Xxxxxxxxxx | xxxxxxxx | xxxxxx | Xxxxx | Xxxxxxx |
3 | xxxxxx | Xxxxxxxx | Xxxxxxx | Xxxxx | xxxxxx | xxxxxxxxxx | Xxxxx | xxxxxxxxxx | xxxxxxxxx | Xxxxxxx | xxxxxxxx | xxxxxxxx | Xxxxxxxxxx | Xxxxxxxx | Xxxxxxxx | xxxxxxxxx | Xxxxxxxxxx | Xxxxxx | Xxxxxxxxx | xxxxx | xxxxxxx | xxxxxxxxx | Xxxxxx |
4 | Xxxxxxx | Xxxxxxxxx | xxxxxxxxx | xxxxxxxxx | Xxxxx | xxxxxxxx | Xxxxxxx | xxxxxxxxx | Xxxxxxx | xxxxx | Xxxxxxx | xxxxxxx | Xxxxx | xxxxxxxxxx | Xxxxxxx | Xxxxx | xxxxxxxxxx | Xxxxxx | xxxxxx | Xxxxxxxxx | xxxxx | Xxxxxxxxxx | xxxxxx |
5 | xxxxx | xxxxxxxx | Xxxxxx | Xxxxxxxxxx | xxxxxxxxx | Xxxxxxxxxx | xxxxxxxx | xxxxx | Xxxxxx | xxxxxxxxxx | xxxxxxxxx | xxxxx | xxxxx | xxxxxxxx | xxxxxx | Xxxxxxxxxx | xxxxxxxxxx | Xxxxx | xxxxxxx | Xxxxxxxx | Xxxxxxx | xxxxx | xxxxxxxx |
6 | xxxxxxxxxx | Xxxxxx | xxxxxxxxx | Xxxxx | xxxxx | xxxxxxxxx | xxxxxxx | Xxxxxxxxx | Xxxxxxx | xxxxxxxxxx | Xxxxx | xxxxxxxxx | xxxxxxx | Xxxxxx | xxxxxxxxx | xxxxx | Xxxxxxx | xxxxxxxxx | Xxxxxxxx | xxxxxxxx | Xxxxxxxx | Xxxxxxxx | xxxxxxxx |
7 | xxxxxxxxx | Xxxxxxx | Xxxxxxxxx | xxxxxxxx | xxxxx | Xxxxxxxxxx | xxxxxxxxxx | xxxxxx | Xxxxx | Xxxxxxx | Xxxxx | Xxxxxx | Xxxxx | Xxxxxxxxx | xxxxxx | xxxxxxxx | Xxxxxxxxx | Xxxxxx | Xxxxxxxxxx | Xxxxxx | Xxxxx | Xxxxxxx | xxxxxxxxx |
8 | Xxxxx | xxxxx | Xxxxxx | xxxxxxxxx | xxxxxxx | xxxxxxxxx | Xxxxxxxxxx | xxxxxxxxx | Xxxxx | Xxxxx | Xxxxxxxxx | xxxxxxxxxx | xxxxxx | xxxxxxxxx | xxxxxxx | Xxxxxxx | Xxxxxxxxxx | Xxxxxxxxxx | Xxxxxxxx | Xxxxxxxxx | xxxxx | Xxxxxxx | xxxxxxxxxx |
9 | Xxxxxxxxx | Xxxxxxxx | xxxxxxxxxx | xxxxxxx | Xxxxxxxx | xxxxx | Xxxxxx | xxxxxx | xxxxxxxx | xxxxxxx | Xxxxx | Xxxxxxxxx | Xxxxx | Xxxxxxx | Xxxxxxxx | xxxxxxxxx | xxxxxxxx | xxxxx | Xxxxxxxxxx | Xxxxxxx | xxxxxxxxx | xxxxxxx | xxxxxxxxxx |
10 | xxxxxx | xxxxx | Xxxxxxxxxx | 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 | Xxxxx | xxxxxxxxx | xxxxxxxx | Xxxxxxxx | xxxxxxxx | Xxxxxxx | Xxxxxx | Xxxxxxxxx | Xxxxxxxx | Xxxxxxxxxx | Xxxxxxx | Xxxxxx | Xxxxxxxxxx |
# | _id |
name |
store_name |
store_uuid |
item_link |
store_type |
unit_size |
unit_measurement |
delivery_enabled |
pickup_enabled |
price |
full_price |
product_image |
lineage |
updated |
street_addr |
city |
state |
zipcode |
country |
lat |
lon |
operational_hours |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
1 | xxxxxxxxxx | Xxxxxxxxx | xxxxxx | xxxxxxxxxx | Xxxxx | Xxxxxx | Xxxxxxxxxx | Xxxxxx | Xxxxxxxxx | Xxxxxxxxxx | xxxxxxxxx | Xxxxxxxxx | xxxxxxxxx | Xxxxxxx | xxxxxx | Xxxxx | xxxxxxxxxx | xxxxxx | Xxxxxxxxxx | xxxxxx | Xxxxx | Xxxxxx | xxxxx |
2 | xxxxxxxx | xxxxxxx | Xxxxx | Xxxxxxxx | xxxxxxxxxx | xxxxxx | Xxxxxxxxx | xxxxxx | Xxxxxxxxx | Xxxxxxxxx | xxxxxxxxxx | Xxxxxx | Xxxxx | xxxxxx | xxxxxxx | xxxxxxx | Xxxxx | xxxxxx | Xxxxxxxxxx | xxxxxxxx | xxxxxx | Xxxxx | Xxxxxxx |
3 | xxxxxx | Xxxxxxxx | Xxxxxxx | Xxxxx | xxxxxx | xxxxxxxxxx | Xxxxx | xxxxxxxxxx | xxxxxxxxx | Xxxxxxx | xxxxxxxx | xxxxxxxx | Xxxxxxxxxx | Xxxxxxxx | Xxxxxxxx | xxxxxxxxx | Xxxxxxxxxx | Xxxxxx | Xxxxxxxxx | xxxxx | xxxxxxx | xxxxxxxxx | Xxxxxx |
4 | Xxxxxxx | Xxxxxxxxx | xxxxxxxxx | xxxxxxxxx | Xxxxx | xxxxxxxx | Xxxxxxx | xxxxxxxxx | Xxxxxxx | xxxxx | Xxxxxxx | xxxxxxx | Xxxxx | xxxxxxxxxx | Xxxxxxx | Xxxxx | xxxxxxxxxx | Xxxxxx | xxxxxx | Xxxxxxxxx | xxxxx | Xxxxxxxxxx | xxxxxx |
5 | xxxxx | xxxxxxxx | Xxxxxx | Xxxxxxxxxx | xxxxxxxxx | Xxxxxxxxxx | xxxxxxxx | xxxxx | Xxxxxx | xxxxxxxxxx | xxxxxxxxx | xxxxx | xxxxx | xxxxxxxx | xxxxxx | Xxxxxxxxxx | xxxxxxxxxx | Xxxxx | xxxxxxx | Xxxxxxxx | Xxxxxxx | xxxxx | xxxxxxxx |
6 | xxxxxxxxxx | Xxxxxx | xxxxxxxxx | Xxxxx | xxxxx | xxxxxxxxx | xxxxxxx | Xxxxxxxxx | Xxxxxxx | xxxxxxxxxx | Xxxxx | xxxxxxxxx | xxxxxxx | Xxxxxx | xxxxxxxxx | xxxxx | Xxxxxxx | xxxxxxxxx | Xxxxxxxx | xxxxxxxx | Xxxxxxxx | Xxxxxxxx | xxxxxxxx |
7 | xxxxxxxxx | Xxxxxxx | Xxxxxxxxx | xxxxxxxx | xxxxx | Xxxxxxxxxx | xxxxxxxxxx | xxxxxx | Xxxxx | Xxxxxxx | Xxxxx | Xxxxxx | Xxxxx | Xxxxxxxxx | xxxxxx | xxxxxxxx | Xxxxxxxxx | Xxxxxx | Xxxxxxxxxx | Xxxxxx | Xxxxx | Xxxxxxx | xxxxxxxxx |
8 | Xxxxx | xxxxx | Xxxxxx | xxxxxxxxx | xxxxxxx | xxxxxxxxx | Xxxxxxxxxx | xxxxxxxxx | Xxxxx | Xxxxx | Xxxxxxxxx | xxxxxxxxxx | xxxxxx | xxxxxxxxx | xxxxxxx | Xxxxxxx | Xxxxxxxxxx | Xxxxxxxxxx | Xxxxxxxx | Xxxxxxxxx | xxxxx | Xxxxxxx | xxxxxxxxxx |
9 | Xxxxxxxxx | Xxxxxxxx | xxxxxxxxxx | xxxxxxx | Xxxxxxxx | xxxxx | Xxxxxx | xxxxxx | xxxxxxxx | xxxxxxx | Xxxxx | Xxxxxxxxx | Xxxxx | Xxxxxxx | Xxxxxxxx | xxxxxxxxx | xxxxxxxx | xxxxx | Xxxxxxxxxx | Xxxxxxx | xxxxxxxxx | xxxxxxx | xxxxxxxxxx |
10 | xxxxxx | xxxxx | Xxxxxxxxxx | 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 | Xxxxx | xxxxxxxxx | xxxxxxxx | Xxxxxxxx | xxxxxxxx | Xxxxxxx | Xxxxxx | Xxxxxxxxx | Xxxxxxxx | Xxxxxxxxxx | Xxxxxxx | Xxxxxx | Xxxxxxxxxx |
# | name |
_id |
lineage |
image |
price |
store_name |
store_uuid |
link |
local_hours |
pickup_enabled |
delivery_enabled |
store_type |
updated |
street_addr |
city |
state |
zipcode |
country |
lat |
lon |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
1 | xxxxxxxxxx | Xxxxxxxxx | xxxxxx | xxxxxxxxxx | Xxxxx | Xxxxxx | Xxxxxxxxxx | Xxxxxx | Xxxxxxxxx | Xxxxxxxxxx | xxxxxxxxx | Xxxxxxxxx | xxxxxxxxx | Xxxxxxx | xxxxxx | Xxxxx | xxxxxxxxxx | xxxxxx | Xxxxxxxxxx | xxxxxx |
2 | Xxxxx | Xxxxxx | xxxxx | xxxxxxxx | xxxxxxx | Xxxxx | Xxxxxxxx | xxxxxxxxxx | xxxxxx | Xxxxxxxxx | xxxxxx | Xxxxxxxxx | Xxxxxxxxx | xxxxxxxxxx | Xxxxxx | Xxxxx | xxxxxx | xxxxxxx | xxxxxxx | Xxxxx |
3 | xxxxxx | Xxxxxxxxxx | xxxxxxxx | xxxxxx | Xxxxx | Xxxxxxx | xxxxxx | Xxxxxxxx | Xxxxxxx | Xxxxx | xxxxxx | xxxxxxxxxx | Xxxxx | xxxxxxxxxx | xxxxxxxxx | Xxxxxxx | xxxxxxxx | xxxxxxxx | Xxxxxxxxxx | Xxxxxxxx |
4 | Xxxxxxxx | xxxxxxxxx | Xxxxxxxxxx | Xxxxxx | Xxxxxxxxx | xxxxx | xxxxxxx | xxxxxxxxx | Xxxxxx | Xxxxxxx | Xxxxxxxxx | xxxxxxxxx | xxxxxxxxx | Xxxxx | xxxxxxxx | Xxxxxxx | xxxxxxxxx | Xxxxxxx | xxxxx | Xxxxxxx |
5 | xxxxxxx | Xxxxx | xxxxxxxxxx | Xxxxxxx | Xxxxx | xxxxxxxxxx | Xxxxxx | xxxxxx | Xxxxxxxxx | xxxxx | Xxxxxxxxxx | xxxxxx | xxxxx | xxxxxxxx | Xxxxxx | Xxxxxxxxxx | xxxxxxxxx | Xxxxxxxxxx | xxxxxxxx | xxxxx |
6 | Xxxxxx | xxxxxxxxxx | xxxxxxxxx | xxxxx | xxxxx | xxxxxxxx | xxxxxx | Xxxxxxxxxx | xxxxxxxxxx | Xxxxx | xxxxxxx | Xxxxxxxx | Xxxxxxx | xxxxx | xxxxxxxx | xxxxxxxxxx | Xxxxxx | xxxxxxxxx | Xxxxx | xxxxx |
7 | xxxxxxxxx | xxxxxxx | Xxxxxxxxx | Xxxxxxx | xxxxxxxxxx | Xxxxx | xxxxxxxxx | xxxxxxx | Xxxxxx | xxxxxxxxx | xxxxx | Xxxxxxx | xxxxxxxxx | Xxxxxxxx | xxxxxxxx | Xxxxxxxx | Xxxxxxxx | xxxxxxxx | xxxxxxxxx | Xxxxxxx |
8 | Xxxxxxxxx | xxxxxxxx | xxxxx | Xxxxxxxxxx | xxxxxxxxxx | xxxxxx | Xxxxx | Xxxxxxx | Xxxxx | Xxxxxx | Xxxxx | Xxxxxxxxx | xxxxxx | xxxxxxxx | Xxxxxxxxx | Xxxxxx | Xxxxxxxxxx | Xxxxxx | Xxxxx | Xxxxxxx |
9 | xxxxxxxxx | Xxxxx | xxxxx | Xxxxxx | xxxxxxxxx | xxxxxxx | xxxxxxxxx | Xxxxxxxxxx | xxxxxxxxx | Xxxxx | Xxxxx | Xxxxxxxxx | xxxxxxxxxx | xxxxxx | xxxxxxxxx | xxxxxxx | Xxxxxxx | Xxxxxxxxxx | Xxxxxxxxxx | Xxxxxxxx |
10 | 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 | Xxxxxxxxx | xxxxxxx | Xxxxxx | Xxxxx | Xxxxxxxx | xxxxxxxxx | xxxxxxxx | Xxxxxx | xxxxxxxxxx | xxxxxxxxx |
Data Dictionary
Attribute | Type | Example | Mapping |
---|---|---|---|
String | Two Medium Pizzas Four Toppings Each With A Pop (2 L) | Product ID | |
String | 545a9727-96c5-49a1-a04d-6dd3eb2286d8:cef5a720-e333-4274-b... | Product Name | |
lineage
|
String | [{'category_id': '069a0717-56a8-4355-ab79-c13c511b6b9d', ... | |
image
|
|||
price
|
Integer | 3245 | |
store_name
|
String | Tito's Pizza | |
String | 545a9727-96c5-49a1-a04d-6dd3eb2286d8 | POI ID | |
String | https://www.skipthedishes.com/-main-street | URL | |
local_hours
|
String | {'Monday': 'Closed', 'Tuesday': '11:15AM - 11:45PM', 'Wed... | |
pickup_enabled
|
Boolean | t | |
delivery_enabled
|
Boolean | t | |
store_type
|
String | restaurant | |
updated
|
String | 01/22/2025 | |
street_addr
|
String | 69 Main St S | |
city
|
String | Brant | |
state
|
String | ON | |
zipcode
|
String | N0E 1N0 | |
country
|
String | CA | |
Float | 43.2418813 | Latitude | |
lon
|
Float | -80.25221359999999 |
Attribute | Type | Example | Mapping |
---|---|---|---|
String | 10052:566560 | Product ID | |
String | Fridababy Easy Grip Electric Nail Trimmer | Product Name | |
String | CVS | POI Name | |
store_uuid
|
Integer | 10052 | |
String | https://www.cvs.com/shop/fridababy-easy-grip-electric-nai... | Product URL | |
store_type
|
String | grocery | |
unit_size
|
Float | 1.0 | |
unit_measurement
|
String | oz | |
delivery_enabled
|
Boolean | t | |
pickup_enabled
|
Boolean | t | |
price
|
Integer | 3499 | |
full_price
|
Integer | 3499 | |
product_image
|
String | https://www.cvs.com/bizcontent/merchandising/productimage... | |
lineage
|
String | [{'name': 'Baby & Kids', 'uuid': 'cat2024', 'url': ''}, {... | |
updated
|
String | 01/23/2025 | |
street_addr
|
String | 1515 Sheridan Rd. | |
String | Wilmette | City Name | |
String | IL | State Abbreviation | |
Integer | 60091 | ZIP Code | |
country
|
String | US | |
Float | 42.08661 | Latitude | |
lon
|
Float | -87.70188 | |
String | {'Monday': '08:00AM - 08:00AM', 'Tuesday': '08:00AM - 08:... | POI Opening Hours |
Attribute | Type | Example | Mapping |
---|---|---|---|
_id
|
String | 100:89194258 | |
name
|
String | Monster Jam Grave Digger RC Monster Truck 1:64 Scale | |
store_name
|
String | Target | |
store_uuid
|
Integer | 100 | |
item_link
|
String | https://www.target.com/p/monster-jam-grave-digger-rc-mons... | |
store_type
|
String | grocery | |
unit_size
|
Float | 1.0 | |
unit_measurement
|
|||
delivery_enabled
|
Boolean | t | |
pickup_enabled
|
Boolean | t | |
price
|
Integer | 1499 | |
full_price
|
Integer | 2499 | |
product_image
|
String | https://target.scene7.com/is/image/Target/GUEST_18a4b378-... | |
lineage
|
String | [{'name': 'Toys', 'uuid': '5xtb0', 'url': ''}, {'name': '... | |
updated
|
String | 12/18/2024 | |
street_addr
|
String | 13201 Ridgedale Dr | |
city
|
String | Minnetonka | |
state
|
String | MN | |
zipcode
|
Integer | 55305 | |
country
|
String | US | |
lat
|
Float | 44.970157 | |
lon
|
Float | -93.447411 | |
operational_hours
|
String | {'Monday': '07:00AM - 11:45PM', 'Tuesday': '07:00AM - 11:... |
Attribute | Type | Example | Mapping |
---|---|---|---|
name
|
String | Sausage Mcmuffin | |
_id
|
String | 36677:78#0 | |
lineage
|
String | [{'category_id': '301', 'category_name': 'Mcvalue Menu'}] | |
image
|
String | https://us-prod5-digitalasset.s3.amazonaws.com/MO_202411_... | |
price
|
Integer | 0 | |
store_name
|
String | McDonald's | |
store_uuid
|
Integer | 36677 | |
link
|
String | https://www.mcdonalds.com/us/en-us/location/ca/san-franci... | |
local_hours
|
String | {'Monday': '06:00AM - 12:00AM', 'Tuesday': '06:00AM - 12:... | |
pickup_enabled
|
Boolean | t | |
delivery_enabled
|
Boolean | t | |
store_type
|
String | restaurant | |
updated
|
String | 01/22/2025 | |
street_addr
|
String | 441 Sutter St | |
city
|
String | San Francisco | |
state
|
String | CA | |
zipcode
|
Integer | 94108 | |
country
|
String | US | |
lat
|
Float | 37.789217 | |
lon
|
Float | -122.407641 |
Description
Country Coverage
History
Volume
1 billion | Records |
1 million | Stores |
100 million | SKUs |
Pricing
Suitable Company Sizes
Delivery
Use Cases
Categories
Related Searches
Related Products
Frequently asked questions
What is Large Language Model (LLM) Data Machine Learning (ML) Data AI Training Data (RAG) for 1M+ Global Grocery, Restaurant, and Retail Stores?
Comprehensive training data on 1M+ stores across the US & Canada. Includes detailed menus, inventory, pricing, and availability. Ideal for AI/ML models, powering retrieval-augmented generation, search, and personalization systems.
What is Large Language Model (LLM) Data Machine Learning (ML) Data AI Training Data (RAG) for 1M+ Global Grocery, Restaurant, and Retail Stores used for?
This product has 5 key use cases. MealMe recommends using the data for Artificial Intelligence (AI), Machine Learning (ML), Deep Learning, Data-Efficient Machine Learning, and LLM Training. Global businesses and organizations buy Machine Learning (ML) Data from MealMe to fuel their analytics and enrichment.
Who can use Large Language Model (LLM) Data Machine Learning (ML) Data AI Training Data (RAG) for 1M+ Global Grocery, Restaurant, and Retail Stores?
This product is best suited if you’re a Small Business, Medium-sized Business, or Enterprise looking for Machine Learning (ML) Data. Get in touch with MealMe to see what their data can do for your business and find out which integrations they provide.
How far back does the data in Large Language Model (LLM) Data Machine Learning (ML) Data AI Training Data (RAG) for 1M+ Global Grocery, Restaurant, and Retail Stores go?
This product has 1 years of historical coverage. It can be delivered on a secondly, minutely, hourly, daily, weekly, monthly, quarterly, yearly, real-time, and on-demand basis.
Which countries does Large Language Model (LLM) Data Machine Learning (ML) Data AI Training Data (RAG) for 1M+ Global Grocery, Restaurant, and Retail Stores cover?
This product includes data covering 250 countries like USA, China, Japan, Germany, and India. MealMe is headquartered in United States of America.
How much does Large Language Model (LLM) Data Machine Learning (ML) Data AI Training Data (RAG) for 1M+ Global Grocery, Restaurant, and Retail Stores cost?
Pricing information for Large Language Model (LLM) Data Machine Learning (ML) Data AI Training Data (RAG) for 1M+ Global Grocery, Restaurant, and Retail Stores is available by getting in contact with MealMe. Connect with MealMe to get a quote and arrange custom pricing models based on your data requirements.
How can I get Large Language Model (LLM) Data Machine Learning (ML) Data AI Training Data (RAG) for 1M+ Global Grocery, Restaurant, and Retail Stores?
Businesses can buy Machine Learning (ML) Data from MealMe and get the data via S3 Bucket, SFTP, Email, UI Export, REST API, SOAP API, Streaming API, and Feed API. Depending on your data requirements and subscription budget, MealMe can deliver this product in .bin, .json, .xml, .csv, .xls, .sql, and .txt format.
What is the data quality of Large Language Model (LLM) Data Machine Learning (ML) Data AI Training Data (RAG) for 1M+ Global Grocery, Restaurant, and Retail Stores?
You can compare and assess the data quality of MealMe using Datarade’s data marketplace.
What are similar products to Large Language Model (LLM) Data Machine Learning (ML) Data AI Training Data (RAG) for 1M+ Global Grocery, Restaurant, and Retail Stores?
This product has 3 related products. These alternatives include AI & ML Training Data 800M Profiles for LLMs, Generative AI, NLP & Predictive Models, Foundation Model Data Collection and Data Annotation Large Language Model(LLM) Data SFT Data Red Teaming Services, and FileMarket 20,000 Voice Memos Multilingual Training Data for Conversational AI Machine Learning (ML) Data. You can compare the best Machine Learning (ML) Data providers and products via Datarade’s data marketplace and get the right data for your use case.