Opah Labs | Restaurant & Food Delivery Transaction Data | North America | Bi-Weekly Updates (Consumer Data w/ 965M Records) | 3227
# | total |
checklistorder |
durationtransit |
productsquantity |
plaza |
durationdriverinbranch |
durationautomaticassignment |
publicid |
discount |
ispaid |
currency |
branch |
tags |
paidwith |
durationbranchdispatch |
folio |
sdc_received_at |
durationorderwaiting |
customer |
sdc_batched_at |
sdc_extracted_at |
ordertype |
durationcompleted |
durationaccepted |
multiorder |
change |
v |
durationonsite |
cancelationreason |
synctofullorderat |
branchsupport |
tip |
sdc_table_version |
createdat |
durationsupplied |
paymentmethod |
updatedat |
shoppingcar |
status |
prescriptionaction |
sdc_sequence |
history |
subtotal |
comments |
id |
endedat |
barcode |
tax |
scheduleddate |
statusbranch |
realdistancefromdrivertobranch |
realdistancefrombranchtoorder |
origin |
geofences |
linealdistancefromdrivertobranch |
timeaproxfrombranchtoorder |
linealdistancefrombranchtoorder |
timeaproxfromdrivertobranch |
isattendedbyexternalservice |
isassignedtoexternalservice |
isvoucher |
externalid |
driverassignedat |
etaalerts |
etametrics |
durationbranchsupplied |
durationbranchinpackaged |
durationbranchinprogress |
reassignreasonhistory |
filemedia |
driverassignedby |
driver |
completedreason |
createdathistoric |
comment |
billinginformation |
medic |
wallet |
thirdpartyservice |
user |
tip_fl |
ticket |
signature |
rate |
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2 | Xxxxx | xxxxxxxxxx | Xxxxxx | xxxxxx | Xxxxxxxxx | xxxxx | 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 | 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 | Xxxxx | Xxxxxxxxx | xxxxxx | xxxxxxxx | Xxxxxxxxx | Xxxxxx | Xxxxxxxxxx | Xxxxxx | Xxxxx | Xxxxxxx | xxxxxxxxx | Xxxxx | xxxxx | Xxxxxx | xxxxxxxxx | xxxxxxx | xxxxxxxxx | Xxxxxxxxxx |
3 | xxxxxxxxx | Xxxxx | Xxxxx | Xxxxxxxxx | xxxxxxxxxx | xxxxxx | xxxxxxxxx | xxxxxxx | Xxxxxxx | Xxxxxxxxxx | Xxxxxxxxxx | Xxxxxxxx | 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 | 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 |
4 | Xxxxxxxxxx | xxxxxxxxxx | xxxxxxxxxx | Xxxxxxx | Xxxxx | Xxxxx | Xxxxx | Xxxxxxx | xxxxx | xxxxxxxxx | xxxxxxx | Xxxxxxx | xxxxxx | xxxxxxxxxx | xxxxxxxxxx | Xxxxxxx | xxxxxxxxx | Xxxxx | 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 | Xxxxxxxx | xxxxxxxxxx | Xxxxxx | Xxxxxxxxx | Xxxxxxxxxx | xxxxxxx |
5 | Xxxxxxxxxx | Xxxxxxxxx | Xxxxxx | xxxxxxxx | xxxxxxxxxx | xxxxxxxx | Xxxxx | xxxxxxxx | xxxxxxxxxx | xxxxxxxx | Xxxxx | xxxxxxxx | xxxxxx | Xxxxxxxx | xxxxxxxxxx | Xxxxxxx | xxxxxxxxxx | Xxxxxxx | Xxxxxxxxx | xxxxxx | Xxxxx | Xxxxx | Xxxxxx | Xxxxxxxxx | Xxxxxxxxx | xxxxx | Xxxxx | Xxxxxxxxxx | Xxxxxxx | Xxxxxxxxxx | Xxxxxxxx | xxxxxxx | xxxxxxxx | Xxxxxx | Xxxxxxxxx | Xxxxxxxxxx | Xxxxxx | Xxxxxx | Xxxxxxx | xxxxxxxxxx | Xxxxxxx | Xxxxxxxxxx | xxxxx | xxxxxxx | xxxxxxxxx | xxxxxxxxx | xxxxxx | xxxxxx | Xxxxxxxxxx | xxxxxxxxxx | xxxxxxxxx | Xxxxxx | xxxxxxxxxx | Xxxxxxx | xxxxxxxxx | xxxxxxx | Xxxxxxxx | Xxxxxxxx | Xxxxxxx | xxxxxx | xxxxx | xxxxx | Xxxxxxxxx | xxxxx | Xxxxx | Xxxxxx | xxxxxxxxxx | Xxxxxxxx | Xxxxxxxx | Xxxxxxxxx | Xxxxxxxxxx | xxxxxx | Xxxxx | Xxxxxxxx | xxxxxx | Xxxxx | Xxxxxx | xxxxxx | xxxxxxxx | Xxxxxxxx | Xxxxxxxxxx | xxxxxxxxxx | Xxxxx | Xxxxxxx |
6 | Xxxxxxx | Xxxxxx | Xxxxxx | xxxxxxxx | Xxxxxxxxx | Xxxxx | Xxxxxxx | xxxxxxxxx | Xxxxxxxxx | xxxxxxx | Xxxxxxxx | Xxxxxxxxxx | xxxxxx | xxxxxxxxxx | xxxxxx | xxxxxx | Xxxxxxxxxx | xxxxxxx | Xxxxxxxxxx | xxxxx | Xxxxxxxxx | Xxxxxxx | Xxxxxxxxx | Xxxxx | Xxxxxxxx | xxxxxxxxx | xxxxxxxxxx | xxxxx | xxxxxxxxxx | xxxxxxx | xxxxxxxx | Xxxxx | xxxxx | xxxxxx | Xxxxxx | xxxxxxxxxx | xxxxxxxxxx | Xxxxxxxxx | xxxxxxx | Xxxxxxx | Xxxxxxxxxx | Xxxxxxxx | xxxxxx | xxxxxx | Xxxxxx | xxxxxx | xxxxx | Xxxxxxxxx | Xxxxxxxxx | Xxxxxx | Xxxxx | Xxxxxxxxx | Xxxxxx | Xxxxxx | xxxxxx | xxxxx | xxxxxxx | xxxxxxxxxx | xxxxxx | Xxxxxxx | Xxxxx | xxxxxxxxxx | Xxxxx | xxxxxxx | xxxxxxx | Xxxxxxxxxx | Xxxxx | xxxxxxx | Xxxxxxxx | Xxxxxx | xxxxxxxxxx | Xxxxx | Xxxxxxx | xxxxx | xxxxxx | xxxxxx | Xxxxxxxx | xxxxxxx | Xxxxxx | xxxxxxxxxx | Xxxxxxx | xxxxxxxxx | Xxxxxx | xxxxxxxxxx |
7 | xxxxxxxx | xxxxxxxxxx | Xxxxx | Xxxxxx | Xxxxxx | xxxxxx | Xxxxxxxx | Xxxxx | xxxxx | Xxxxxxxxxx | xxxxxx | xxxxx | xxxxxxx | xxxxx | Xxxxxxx | xxxxxxxxxx | Xxxxxxx | xxxxxxxxxx | xxxxxxxxxx | xxxxxxx | xxxxxxx | xxxxxxxxxx | Xxxxxxxxxx | Xxxxxx | xxxxxx | Xxxxxxxxxx | Xxxxxx | Xxxxxx | Xxxxxxx | Xxxxxx | xxxxxxxx | xxxxx | Xxxxxxxxxx | Xxxxx | xxxxxxx | xxxxxxxx | xxxxxxxx | Xxxxxxxx | xxxxxxx | xxxxxx | Xxxxxxxx | xxxxxxx | Xxxxxxxxxx | xxxxxxxx | xxxxxxxx | xxxxxx | Xxxxxxxx | xxxxx | Xxxxx | Xxxxxxxxx | xxxxxxxxx | xxxxxxxxxx | xxxxxxxxx | xxxxxxx | Xxxxxxxx | Xxxxx | Xxxxxxxx | Xxxxxxxxx | xxxxxxxxxx | Xxxxxx | xxxxxxxxx | Xxxxxx | Xxxxxxxxxx | Xxxxxx | xxxxxxxx | xxxxxx | xxxxxxxxxx | Xxxxxxx | xxxxxxxxxx | Xxxxxx | Xxxxxx | Xxxxxxxxxx | xxxxxxxxxx | Xxxxxxxxx | xxxxxxxx | xxxxxxx | xxxxx | Xxxxxxx | xxxxxxxxx | Xxxxxxx | xxxxxxxx | xxxxxxxxxx | xxxxxxxxx | xxxxxxxx |
8 | xxxxxxxxx | Xxxxx | xxxxx | xxxxxxx | xxxxxxxx | xxxxxx | xxxxxxx | Xxxxx | Xxxxxxxxx | Xxxxxxx | Xxxxxxx | Xxxxxxxx | xxxxxxx | xxxxxxxxx | Xxxxxxxx | xxxxxxxxx | xxxxxxx | xxxxxx | Xxxxxxxxxx | Xxxxxx | Xxxxxxxx | xxxxxxxxxx | Xxxxxxx | xxxxxxxxxx | Xxxxxxxxxx | xxxxxxxxx | xxxxxxxxx | Xxxxxx | Xxxxxxx | Xxxxxxxx | xxxxxxx | xxxxxxx | Xxxxxxxx | xxxxxxx | Xxxxxxx | Xxxxxxx | Xxxxxxxxx | Xxxxx | xxxxx | Xxxxxxx | xxxxxxxxx | Xxxxx | Xxxxxxxx | xxxxxxxxx | Xxxxxx | xxxxxxxx | Xxxxxxxx | Xxxxxxxxxx | Xxxxxxxx | Xxxxxx | xxxxxxxxx | xxxxx | xxxxxx | Xxxxxxxxx | xxxxxxxxx | xxxxxx | xxxxxxxxx | Xxxxxxxx | Xxxxxxxxxx | Xxxxx | Xxxxxxxx | xxxxxxxx | Xxxxxxxxx | Xxxxxxxxx | Xxxxxxxx | Xxxxxxxxx | Xxxxxxx | Xxxxxx | Xxxxxxxx | xxxxxxx | Xxxxxx | Xxxxxx | xxxxxxx | Xxxxxxx | Xxxxx | Xxxxxxxxxx | Xxxxxxxxxx | Xxxxxxxx | Xxxxxxx | Xxxxxxxxx | xxxxxxx | xxxxxxxxxx | Xxxxx | xxxxxxxxx |
9 | Xxxxxxx | xxxxxxxx | Xxxxxx | xxxxxxx | xxxxxxxxx | xxxxxxxxxx | xxxxxxx | xxxxxxxxx | xxxxxxxxxx | Xxxxxxx | Xxxxxxxx | Xxxxxx | Xxxxx | Xxxxxxxxx | Xxxxxxxxx | xxxxx | xxxxxxxxxx | xxxxxxx | xxxxxxx | Xxxxxxxx | Xxxxxxx | xxxxx | Xxxxxx | xxxxxxxx | xxxxxx | xxxxxxx | Xxxxxxxxxx | Xxxxxxxxx | xxxxxxxx | Xxxxxxx | Xxxxxxxxxx | Xxxxxx | Xxxxxxxx | xxxxxxxxx | xxxxxxxx | Xxxxxxxxxx | Xxxxxxx | xxxxxx | xxxxxxxxx | xxxxxxx | xxxxxx | Xxxxxx | xxxxxxxx | xxxxxxxx | xxxxxxxxxx | xxxxxx | Xxxxxxxx | xxxxxxx | xxxxxxxxx | xxxxxx | Xxxxx | Xxxxxx | Xxxxxxxxxx | xxxxx | xxxxxxxx | xxxxxxxx | Xxxxx | xxxxxxx | xxxxxxx | xxxxxxx | xxxxxxxxxx | xxxxx | Xxxxxxx | xxxxx | Xxxxxxxxx | xxxxx | Xxxxxxx | xxxxxxxx | Xxxxx | Xxxxxxxxx | Xxxxx | xxxxxxx | Xxxxxxx | xxxxxxx | xxxxx | Xxxxxxxxx | Xxxxxxx | Xxxxxx | Xxxxxx | xxxxx | xxxxxxxx | Xxxxxxxxx | xxxxxxxxx | xxxxx |
10 | xxxxxxx | Xxxxxxxx | xxxxx | Xxxxxxxx | xxxxxx | xxxxxxxxxx | xxxxx | xxxxxx | xxxxxx | Xxxxx | Xxxxxx | xxxxxxxxx | Xxxxxxxxx | Xxxxxx | xxxxxxxx | xxxxxxxx | xxxxxxx | xxxxxxxxx | Xxxxxxxx | Xxxxxxxxxx | Xxxxxxx | Xxxxxxxxx | xxxxxxx | xxxxxx | Xxxxx | xxxxx | Xxxxxxxxx | xxxxxxxxx | xxxxxxxxxx | xxxxxxxxx | xxxxxxx | Xxxxxxx | xxxxx | xxxxxx | xxxxxx | xxxxxxx | Xxxxxx | xxxxxx | Xxxxxxxx | Xxxxxxx | xxxxxxx | Xxxxxxx | Xxxxxxxx | xxxxxxxx | Xxxxxxxxx | xxxxxxxxxx | Xxxxxxxxx | Xxxxxxxxxx | Xxxxxxxxxx | xxxxx | Xxxxxx | Xxxxxxxx | Xxxxxxx | xxxxxxxxxx | Xxxxxxxxx | xxxxxxxxx | Xxxxxxxx | Xxxxxxxx | Xxxxx | Xxxxxx | Xxxxxxxxx | xxxxx | xxxxxxxxxx | Xxxxxxx | xxxxxxx | Xxxxx | xxxxxxxx | Xxxxxx | xxxxx | Xxxxxxx | Xxxxxx | Xxxxxxxxx | Xxxxx | Xxxxxxx | xxxxxx | xxxxxx | xxxxxxxxx | xxxxx | Xxxxxxx | Xxxxxxxx | xxxxx | Xxxxxxxxx | Xxxxxxxxx | Xxxxxxxxx |
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Data Dictionary
Attribute | Type | Example | Mapping |
---|---|---|---|
total
|
Integer | 264 | |
checklistorder
|
String | [{'value': {'_id': '61d2263bd4972b6e39d76b61', 'type': 'F... | |
durationtransit
|
Integer | 4448 | |
productsquantity
|
Integer | 9 | |
plaza
|
String | REDACTED | |
durationdriverinbranch
|
Integer | 13 | |
durationautomaticassignment
|
Integer | 3077 | |
publicid
|
Integer | 500782443 | |
discount
|
Float | 8.16 | |
ispaid
|
Boolean | t | |
currency
|
String | MXN | |
branch
|
String | REDACTED | |
tags
|
String | [{}, {}, {}, {}, {}, {'value': 'CLIENTE PUBLICO GENERAL'}... | |
paidwith
|
Integer | 1700 | |
durationbranchdispatch
|
Integer | 472 | |
folio
|
String | 33ET4L1 | |
sdc_received_at
|
DateTime | 2022-03-23T14:51:57+00:00 | |
durationorderwaiting
|
Integer | 237 | |
customer
|
String | REDACTED | |
sdc_batched_at
|
DateTime | 2021-03-11T01:35:54+00:00 | |
sdc_extracted_at
|
DateTime | 2022-04-04T16:51:45+00:00 | |
ordertype
|
String | DELIVERY | |
durationcompleted
|
Integer | 1484 | |
durationaccepted
|
Integer | 2735 | |
multiorder
|
Boolean | t | |
change
|
Integer | 132 | |
v
|
Integer | 0 | |
durationonsite
|
Integer | 5480 | |
cancelationreason
|
String | FARMACIA NO CUENTA CON PRODUCTO | |
synctofullorderat
|
DateTime | 2021-03-02T07:06:54+00:00 | |
branchsupport
|
String | REDACTED | |
tip
|
Integer | 50 | |
sdc_table_version
|
Integer | 1615423902272 | |
createdat
|
DateTime | 2021-11-08T17:10:35+00:00 | |
durationsupplied
|
Integer | 1580 | |
paymentmethod
|
String | TARJETA | |
updatedat
|
DateTime | 2021-06-20T16:29:53+00:00 | |
shoppingcar
|
String | {'products': [{'value': {'sku': '01012', 'tax': 0, 'name'... | |
status
|
String | CANCELED | |
prescriptionaction
|
String | NONE | |
sdc_sequence
|
Integer | 1615430099158335030 | |
history
|
String | REDACTED | |
subtotal
|
Float | 218.5 | |
comments
|
String | REDACTED | |
id
|
String | 5f32faf7c54f5b35b44fdd30 | |
endedat
|
DateTime | 2020-05-06T03:06:40+00:00 | |
barcode
|
String | 110291727|501941178APP | |
tax
|
Integer | 21 | |
scheduleddate
|
DateTime | 2021-07-25T13:30:59+00:00 | |
statusbranch
|
String | BRANCH_DISPATCH | |
realdistancefromdrivertobranch
|
Float | 3263.1 | |
realdistancefrombranchtoorder
|
Integer | 1307 | |
origin
|
String | LD-EXPRESS | |
geofences
|
String | REDACTED | |
linealdistancefromdrivertobranch
|
Float | 2525.59672 | |
timeaproxfrombranchtoorder
|
Float | 570.4 | |
linealdistancefrombranchtoorder
|
Float | 1264.527235 | |
timeaproxfromdrivertobranch
|
Float | 304.4 | |
isattendedbyexternalservice
|
Boolean | t | |
isassignedtoexternalservice
|
Boolean | t | |
isvoucher
|
Boolean | t | |
externalid
|
String | [{'value': {'name': 'INTEGRACIONES SERVICE-BUS', 'referen... | |
driverassignedat
|
DateTime | 2021-09-29T23:34:15+00:00 | |
etaalerts
|
String | REDACTED | |
etametrics
|
String | {'ordersdrivercount': '0', 'ordersactivebyplaza': '55', '... | |
durationbranchsupplied
|
Integer | 0 | |
durationbranchinpackaged
|
Integer | 0 | |
durationbranchinprogress
|
Integer | 309 | |
reassignreasonhistory
|
String | REDACTED | |
filemedia
|
String | REDACTED | |
driverassignedby
|
String | REDACTED | |
driver
|
String | REDACTED | |
completedreason
|
String | ENTREGADO CON DIRECCIN INCORRECTA | |
createdathistoric
|
DateTime | 2022-04-13T02:04:21+00:00 | |
comment
|
String | REDACTED | |
billinginformation
|
String | REDACTED | |
medic
|
String | REDACTED | |
wallet
|
Integer | 4600678945984 | |
thirdpartyservice
|
String | Mensajeros Urbanos | |
user
|
String | REDACTED | |
tip_fl
|
Float | 0.01 | |
ticket
|
String | Farmacias Roma | |
signature
|
String | REDACTED | |
rate
|
String | {'orderrate': '4', 'driverrate': '3', 'ordercomment': 'Fo... |
Description
Geography
History
Volume
965 million | Records |
Pricing
License | Starts at |
---|---|
One-off purchase | Not available |
Monthly License | Not available |
Yearly License | Available |
Usage-based | Not available |
Suitable Company Sizes
Quality
Delivery
Use Cases
Categories
Related Searches
Related Products
Frequently asked questions
What is Opah Labs Restaurant & Food Delivery Transaction Data North America Bi-Weekly Updates (Consumer Data w/ 965M Records) 3227?
Streamline food delivery operations with software enriched by comprehensive Restaurant & Food Delivery Transaction Data. Gain valuable insights into driver info, transit times, products, payments, and customer behavior to enhance delivery efficiency and customer satisfaction.
What is Opah Labs Restaurant & Food Delivery Transaction Data North America Bi-Weekly Updates (Consumer Data w/ 965M Records) 3227 used for?
This product has 3 key use cases. Opah Labs recommends using the data for vehicle location, Pharma, and Restaurant & Food Delivery Transaction. Global businesses and organizations buy Vehicle Location Data from Opah Labs to fuel their analytics and enrichment.
Who can use Opah Labs Restaurant & Food Delivery Transaction Data North America Bi-Weekly Updates (Consumer Data w/ 965M Records) 3227?
This product is best suited if you’re a Small Business, Medium-sized Business, or Enterprise looking for Vehicle Location Data. Get in touch with Opah Labs to see what their data can do for your business and find out which integrations they provide.
How far back does the data in Opah Labs Restaurant & Food Delivery Transaction Data North America Bi-Weekly Updates (Consumer Data w/ 965M Records) 3227 go?
This Data Feed has 8 years of historical coverage. It can be delivered on a weekly and monthly basis.
Which countries does Opah Labs Restaurant & Food Delivery Transaction Data North America Bi-Weekly Updates (Consumer Data w/ 965M Records) 3227 cover?
This product includes data covering 2 countries like USA and Mexico. Opah Labs is headquartered in United States of America.
How much does Opah Labs Restaurant & Food Delivery Transaction Data North America Bi-Weekly Updates (Consumer Data w/ 965M Records) 3227 cost?
Pricing information for Opah Labs Restaurant & Food Delivery Transaction Data North America Bi-Weekly Updates (Consumer Data w/ 965M Records) 3227 is available by getting in contact with Opah Labs. Connect with Opah Labs to get a quote and arrange custom pricing models based on your data requirements.
How can I get Opah Labs Restaurant & Food Delivery Transaction Data North America Bi-Weekly Updates (Consumer Data w/ 965M Records) 3227?
Businesses can buy Vehicle Location Data from Opah Labs and get the data via S3 Bucket. Depending on your data requirements and subscription budget, Opah Labs can deliver this product in .json and .csv format.
What is the data quality of Opah Labs Restaurant & Food Delivery Transaction Data North America Bi-Weekly Updates (Consumer Data w/ 965M Records) 3227?
Opah Labs has reported that this product has the following quality and accuracy assurances: 100% match rate. You can compare and assess the data quality of Opah Labs using Datarade’s data marketplace.
What are similar products to Opah Labs Restaurant & Food Delivery Transaction Data North America Bi-Weekly Updates (Consumer Data w/ 965M Records) 3227?
This Data Feed has 3 related products. These alternatives include Opah Labs Pharma Data North America Bi-Weekly Updates (Consumer Data w/ 965M Records) 3227, Grepsr Food Menu, Prices, Deliveries, and Reviews from Food Delivery Sites Global Coverage with Custom and On-demand Datasets, and Webautomation Ebay Data Web Scraping Data Analyze Market Trends, Monitor Competitor Performance Real-Time Updates GDPR Compliant. You can compare the best Vehicle Location Data providers and products via Datarade’s data marketplace and get the right data for your use case.