Create or edit a connection create-or-edit-a-connection

Choose a sandbox in Experience Platform that contains the dataset/s to which you want to create a connection.

Adobe Experience Platform provides sandboxes which partition a single Platform instance into separate virtual environments to help develop and evolve digital experience applications. You can think of sandboxes as “data silos” that contain datasets. Sandboxes are used to control access to datasets.

Once you have selected the sandbox, the left rail shows all the datasets in that sandbox that you can pull from.

This checkbox, if checked, lets you define Customer Journey Analytics data retention as a rolling window in months (1 month, 3 months, 6 months, and so on), at the connection level.

Data retention is based on event dataset timestamps and applies to event datasets only. No rolling data window setting exists for profile or lookup datasets, since there are no applicable timestamps. However, if your connection includes any profile or lookup datasets (besides one or more event datasets), that data is retained for the same time period.

The main benefit is that you store or report only on data that is applicable and useful and delete older data that is no longer useful. It helps you stay under your contract limits and reduces the risk of overage cost.

If you leave the default (unchecked), the Adobe Experience Platform data retention setting supersedes the retention period. If you have 25 months’ worth of data in Experience Platform, Customer Journey Analytics gets 25 months of data through backfill. If you deleted 10 of those months in Platform, Customer Journey Analytics would retain the remaining 15 months.

Select one or more datasets that you want to pull into Customer Journey Analytics and select Add.

(If you have many datasets to choose from, you can search for the right one(s) using the Search datasets search bar above the list of datasets.)

Select a Person ID from the drop-down list of available identities. These identities were defined in the dataset schema in the Experience Platform. See below for information on how to use Identity Map as a Person ID.

IMPORTANT: If there are no Person IDs to choose from, that means one or more Person IDs have not been defined in the schema. View this video on how to define an identity in Experience Platform.

You can request to backfill the data in a dataset. For example, you can request to backfill the last 7 days worth of data. Configure the dataset correctly and test your connection. If everything looks good, you can backfill all the remaining data with ease.

In addition, you can enable the import of new data by dataset.

Only available for event and profile datasets. Select a Person ID from the drop-down list of available identities. These identities were defined in the dataset schema in the Experience Platform. See below for information on how to use Identity Map as a Person ID.

If there are no Person IDs to choose from, that means one or more Person IDs have not been defined in the schema. See Define identity fields in the UI for more information.

The value for the selected Person ID is considered to be case sensitive. For example, abc123 and ABC123 are two different values.

Select a type of data source.
Types of data sources include:

• Web data
• Mobile App data
• POS data
• CRM data
• Survey data
• Call Center data
• Product data
• Accounts data
• Transaction data
• Customer Feedback data
• Other

This field is used to survey the types of data sources in use.

Enable Backfill all existing data to ensure that all existing data is backfilled.

Select Request backfill to backfill historical data for a specific period. You can define up to 10 dataset backfill periods.

1. Define the period by entering start and end data or selecting dates using .
2. Select Queue backfill to add the backfill to the list, or Cancel to cancel.

For each entry, select to edit the period, or select to delete the entry.

On backfills:

• You can backfill each dataset individually.
• You prioritize new data added to a dataset in the connection, so this new data has the lowest latency.
• Any backfill (historical) data is imported at a slower rate. The amount of historical data influences the latency.
• The Analytics source connector imports up to 13 months of data (irrespective of size) for production sandboxes. The backfill in non-production sandboxes is limited to 3 months.

Possible status indicators are:

• Success
• X backfill(s) processing
• Off

Select AVG(A.total_events) from (Select DISTINCT COUNT (*) as total_events, date(TIMESTAMP) from analytics_demo_data GROUP BY 2 Having total_events>0) A;