LinkedIn Ads
Guide to integrate your LinkedIn Ads with Sprinkle
Datasource Concepts
Before setting up the datasource, learn about datasource concepts here
Step by Step Guide
STEP-1: Configure Connection
To learn about Connection, refer here
Log into Sprinkle application
Navigate to Datasources -> Connections Tab -> New Connection ->
Select LinkedIn Ads
Provide all the mandatory details
Name: Name to identify this connection
Connect to LinkedIn
Test Connection
Create
STEP-2: Configure Datasource
To learn about datasource, refer here
Navigate to Datasources -> Datasources Tab -> Add ->
Select LinkedIn Ads
Provide the name -> Create
Connection Tab:
From the drop-down, select the name of connection created in STEP-2
Update
STEP-3: Create Dataset
Datasets Tab: To learn about Dataset, refer here. Add Dataset for each report/dataset that you want to integrate, providing following details
Report Type (Required) : Select the API through which you want the result. Read more from LinkedIn api docs. Select report type from any one of the following:
Accounts
Account_Users
AdAccount Id: Select from the drop-down
Campaign_Groups
AdAccount Id: Select from the drop-down
Campaigns
AdAccount Id: Select from the drop-down
SponsoredUpdateCreativeVariables
AdAccount Id: Select from the drop-down
Creatives
AdAccount Id: Select from the drop-down
Conversions
AdAccount Id: Select from the drop-down
AD_Segments_By_Account
AdAccount Id: Select from the drop-down
AD_Targeting_Facets
AD_Forms
AdAccount Id: Select from the drop-down
AD_Analytics
AdAccount Id: Select from the drop-down
Pivot Values: Pivot of results, by which each report data point is grouped. See about Pivot here. Select from the drop-down.
Metrics: Max. 20 metrics can be selected at a time. See about metrics here.
Start Date: Start Date from which you want to fetch data. Give Start Date in Format yyyy-mm-dd
Ingestion Mode:
Complete: Will download full data in every ingestion from the start date.
Time Granularity: Results grouped by the selected value of Time Granularity. See about Time Granularity in Query Parameters here. Select from ALL, MONTHLY, YEARLY.
Incremental: Will download updated rows in the table, based on start date value in first run and checkpoint value in each run. Having Time Granularity set as DAILY
Window for Backfill: Mention window for backfill, for backfilling metrics in every run to include updates from attribution window. Can take values 1, 7 and 28.
Flatten Level(Required) : Select One Level or Multi Level. In one level, flattening will not be applied on complex type. They will be stored as string. In multi level, flattening will be applied in complex level till they become simple type.
Destination Schema (Required) : Data warehouse schema where the table will be ingested into
Destination Table name (Required) : It is the table name to be created on the warehouse. If not given, sprinkle will create like ds_<datasourcename>_<tablename>
Destination Create Table Clause: Provide additional clauses to warehouse-create table queries such as clustering, partitioning, and more, useful for optimizing DML statements. Learn more on how to use this field.
Create
STEP-4: Run and schedule Ingestion
In the Ingestion Jobs tab:
Trigger the Job, using the Run button
To schedule, enable Auto-Run. Change the frequency if needed
Dataset Fields
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