This page explains how to import data in the Reservation object using a CSV file.
Make sure that you do not attempt to write to the following fields, as these fields are set automatically by Booker25: |
The first option is recommended if you are importing data for Resources in multiple timezones, because then you can apply the same timezone to every time field. If the Reservations you are importing are all in the same timezone as your user, then it does not matter which option you choose.
If you are not familiar with the date formats accepted by Salesforce's Data Loader, please refer to this article: https://developer.salesforce.com/docs/atlas.en-us.dataLoader.meta/dataLoader/supported_data_types.htm |
We have two Resources in two different timezones: Moscow (+3:00) and Bangalore (+5:30).
We are importing two Reservations, one for each Resource. They both start at noon, and they both last one hour.
If we use the first option, we will need to use the user's timezone. Let's say you are located in Amsterdam with timezone +2:00.
The resulting CSV will look something like this:
B25__Title__c | B25__Resource__c | B25__StartLocal__c | B25__EndLocal__c |
---|---|---|---|
Reservation 1 (Moscow) | <Moscow record Id> | 2019-09-03T12:00:00.000+200 | 2019-09-03T13:00:00.000+200 |
Reservation 2 (Bangalore) | <Bangalore record Id> | 2019-09-03T12:00:00.000+200 | 2019-09-03T13:00:00.000+200 |
If we use the second option, our CSV will look something like this (note the different column headers for the time fields):
B25__Title__c | B25__Resource__c | B25__Start__c | B25__End__c |
---|---|---|---|
Reservation 1 (Moscow) | <Moscow record Id> | 2019-09-03T12:00:00.000+300 | 2019-09-03T13:00:00.000+300 |
Reservation 2 (Bangalore) | <Bangalore record Id> | 2019-09-03T12:00:00.000+530 | 2019-09-03T13:00:00.000+530 |
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