Funding Instruments can be used to retrieve details for some or all of funding instruments associated with the current account. Funding instruments determine the budget of a campaign.
You can read more about this on the Twitter marketing API documentation page here
Configuring the Credentials
Select the account credentials which has access to relevant Twitter Ads data from the dropdown menu & Click Next
Data Pipelines Details
- Data Pipeline
Select FundingInstruments from the dropdown
Select one or more accounts from the drop-down
|All accounts which your credentials have access to should be available here. If they are not, please check the credentials selected / configured by you. While you can add multiple accounts, the table size may become too large and so it is advisable to add one account per pipeline and use Union queries in the data warehouse to join the data for consumption|
Select the metrics you would like to fetch from the Twitter Ads platform. You can click on View Schema anytime to see the schema of the table being created.
|Each of the selected metric will create one or more columns in the database table in the destination warehouse.|
Delete or Append
This refers to the manner in which data will get updated in the data warehouse, with 'Delete' selected, the data will be upserted (only new records or records with changes) and with 'Append' selected, all data fetched will be inserted. Recommended to use "Delete" option unless there is a specific requirement.
Default Value: Delete
Scheduling specifies the frequency with which data will get updated in the data warehouse. You can choose between Manual Run, Normal Scheduling or Advance Scheduling.
- Manual Run
If scheduling is not required, you can use the toggle to run the pipeline manually.
- Normal Scheduling
Use the dropdown to select an interval-based hourly, monthly, weekly, or daily frequency.
- Advance Scheduling
Set schedules fine-grained at the level of Months, Days, Hours, and Minutes.
Detailed explanation on scheduling of pipelines can be found here
Dataset & Name
- Dataset Name
Key in the Dataset Name(also serves as the table name in your data destination).Keep in mind, that the name should be unique across the account and the data source. Special characters (except underscore _) and blank spaces are not allowed. It is best to follow a consistent naming scheme for future search to locate the tables.
- Dataset Description
Enter a short description (optional) describing the dataset being fetched by this particular pipeline.
Choose the events for which you’d like to be notified: whether "ERROR ONLY" or "ERROR AND SUCCESS".
Once you have finished click on Finish to save it. Read more about naming and saving your pipelines including the option to save them as templates here
Still have Questions?
We’ll be happy to help you with any questions you might have! Send us an email at email@example.com.
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