Raw Events

The CleverTap SDK tracks the actions users perform in your app or website, such as a user viewing a product, listening to a song, or making a purchase. Events represent these actions that users take with your product. Events are associated with a user profile.

Raw Events pipeline can be used to request and retrieve details of the user events from CleverTap. Read more about this here

Configuring the Credentials

Select the account credentials which has access to relevant CleverTap data from the dropdown menu & Click Next

Credentials not listed in dropdown ?: Click on + Add New for adding new credentials

All accounts which your credentials have access to should be available here. If they are not, please check the credentials selected / configured by you.

Data Pipelines Details

Data Pipeline: Select Raw Events from the dropdown

Setting Parameters

Parameter Description Values

Parameter	Description	Values
Event Name	*Required & Non-editable once the pipeline starts.* An event name can define both the standard and custom events. The standard events include App Launched, App Installed, App Uninstalled, Charged, Notification Viewed, Product Viewed, and UTM Visited.	string (Example: “App Launched”)
No of Days	*Required* Number of days for which you wish to get the data in each run.	Integer value (Recommended value 7)
Insert Mode	*Required* 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. Selecting 'Replace' will ensure the table is dropped and recreated with fresh data on each run. Recommended to use "Upsert" option unless there is a specific requirement.	`Upsert`, `Append`, `Replace` *Default Value:* UPSERT

Event Name

Required & Non-editable once the pipeline starts.

An event name can define both the standard and custom events. The standard events include App Launched, App Installed, App Uninstalled, Charged, Notification Viewed, Product Viewed, and UTM Visited.

string (Example: “App Launched”)

No of Days

Required

Number of days for which you wish to get the data in each run.

Integer value (Recommended value 7)

Insert Mode

Required

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. Selecting 'Replace' will ensure the table is dropped and recreated with fresh data on each run. Recommended to use "Upsert" option unless there is a specific requirement.

Upsert, Append, Replace

Default Value: UPSERT

Datapipeline Scheduling

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 warehouse).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.
Notifications: 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 info@datachannel.co.

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