Manage connections
Once you have created or edited one or more connections, you can manage them in Connections. Connections let you:
- View all your connections at a glance, including the owner, the sandbox, and when the connections were created and modified.
- Edit a connection.
- Delete a connection.
- Create a data view from a connection.
- View all datasets in a connection.
- Check the status of your connection’s datasets and the status of the ingestion process. For example, when is your data available so that you can start with reporting and analysis in Analysis Workspace.
- Identify any data discrepancies due to misconfiguration. Are you missing any rows? If so, what rows are missing and why? Did you misconfigure connections and cause missing data in Customer Journey Analytics?
- Get insights on the usage of ingested and reportable rows across all your connections.
Connections has two interfaces: List and Usage.
List
The List interface is the default interface for Connections. If not selected, select the List tab to access the interface.
The List interface shows a table of all connections available. You can quickly search for a connection using the Search box.
The following columns or icons are available in the table.
To view information about Datasets included, Sandbox, Owner, and more, select next to the connection name.
A popup window displays details.
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Select to:
Edit a connection.
Delete a connection.
Create new data view. To create additional data views for the connection.
One or more links to the datasets that are part of the connection. You can select the dataset hyperlink to view the dataset in the connection. If more datasets are part of the selected connection, select +x more to show a Datasets included panel. This panel shows links to all datasets and an option to search for a specific dataset that is part of the connection.
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Selecting a dataset name opens the dataset in the Experience Platform UI in a new tab.
The status of importing new data for datasets:
) ÌýÌýÌý x On for datasets configured to import new data, and
ÌýÌýÌý x Off for datasets not configured to import new data.
The status for backfill data across datasets.
ÌýÌýÌý x backfills failed for number of failed backfills across datasets,
ÌýÌýÌý x backfills processing for number of processing backfills across datasets,
ÌýÌýÌý x backfills completed for number of completed backfills for datasets, and
ÌýÌýÌý Off in case no backfills are defined for the datasets in the connection.
To configure which columns to display select , which shows the Customize table dialog allowing you turn columns on or off in the table.
Edit a connection
- Select next to the connection name
- Select Edit from the context menu.
Alternatively, you can:
-
Select the connection row.
-
Select Edit from the blue bar.
When editing a connection, you can:
- Start and stop importing new data.
- Rename a connection.
- Refresh the dataset/s.
- Remove dataset/s from the connections.
See Create or edit a connection for more information.
Delete a connection connections-delete
- Select next to the connection name.
- Select Delete.
Alternatively, you can:
-
Select the connection row.
-
Select Delete from the blue bar.
When you delete a connection, a Delete connection panel indicates which data views are deleted and which workspace projects are affected.
Select Continue to delete the connection.
See Deletion implications for more information about deleting a connection.
Create a data view for a connection
-
If no data view is associated with the connection:
- Select next to the connection name.
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If one or more data views are already created for the connection:
- Select next to the connection name.
- Select Create new data view.
Alternatively, you can:
-
Select the connection row.
-
Select Create data view from the blue button bar.
See Create or edit a data view for more information.
Connection details connection-detail
To go to the details for a connection, select a connection name in the connections table.
The Connections details interface provides a detailed view of the status of a connection. You can:
- Check the status of your connection’s datasets and of the ingestion process.
- Identify configuration problems that can cause skipped or deleted records.
- See when the data is available for reporting.
Summarize the event, lookup, profile and summary dataset records that are added, skipped, and deleted, and the number of batches added. These metrics are based on the dataset and date range you have selected.
Select Check detail to show the Check skipped detail popup. The popup lists the number of skipped records and the reason for all event datasets or selected dataset.
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Select popup with more information. For some skipped reasons, like Empty visitor ID, the popup displays Sample PSQL for EQS (Experience Platform for Query Service) you can use in Query Service to query for the skipped records in the dataset. Select Copy sample PSQL for EQS to copy the SQL.
Indicates how many rows were skipped in the selected time period, for the dataset and date range you have selected. Reasons for skipping records include: missing timestamps, missing or invalid person ID, and so forth. Updated every 10 minutes.
Invalid person IDs (such as undefined
, or 00000000
, or any combination of numbers and letters in a Person ID that appear in an event more than 1 million times in a given month) are IDs that cannot be attributed to any specific user or person. These rows cannot be ingested into the system and result in error-prone ingestion and reporting. To fix invalid person IDs, you have 3 options:
- Use Stitching to populate the undefined or all-zero user IDs with valid user IDs.
- Blank out the user ID, which are then kipped during ingestion (preferable to invalid or all-zero user IDs).
- Fix any invalid user IDs in your system before ingesting the data.
Indicates how many rows were deleted in the selected time period, for the dataset and date range you have selected. Someone might have deleted a dataset in Experience Platform, for example. Updated every 10 minutes.
In some scenarios, this value can also include records replaced, as with stitching or some lookup dataset updates. Consider this example:
- You upload one record to an XDM Individual Profile dataset, which Customer Journey Analytics is configured to ingest as profile lookup data. In the connection details, this dataset would display 1 record added.
- You upload a duplicate of the original record into the same AEP dataset, which now contains two records. Customer Journey Analytics ingests the additional record from the profile lookup dataset. Seeing that it has already ingested a profile record in the connection for that person ID, Customer Journey Analytics deletes its earlier version and adds the new profile data. In the connection details, this action would represent 1 record added and 1 record deleted, because Customer Journey Analytics only retains the most recent profile lookup data for any ingested person ID.
- In total, the AEP dataset contains two records that happen to be identical. Separately, the Customer Journey Analytics connection details display the status of its ingested data: 2 records added and 1 record deleted for this profile dataset.
The status of importing new data for the dataset:
ÌýÌýÌý x On if dataset is configured to import new data, and
ÌýÌýÌý x Off if dataset is configured not to import new data import.
The transformation status of applicable B2B lookup datasets. See Transform datasets for B2B lookups for more information.
ÌýÌýÌý x On for applicable datasets enabled for transformation,
ÌýÌýÌý x Off for applicable datasets not enabled for transformation, and
N/A for all other datasets, not applicable for transformation.
The status of backfill data for the dataset.
ÌýÌýÌý x backfills failed for number of failed backfills,
ÌýÌýÌý x backfills processing for number of processing backfills,
ÌýÌýÌý x backfills completed for number of backfills completed, and
ÌýÌýÌý Off in case backfills are not configured.
The status of importing new data for the dataset:
ÌýÌýÌý x On if the dataset is configured to import new data, and
ÌýÌýÌý x Off if the dataset is configured not to import new data.
The status of backfill data for the dataset.
ÌýÌýÌý x backfills failed for number of failed backfills,
ÌýÌýÌý x backfills processing for number of processing backfills,
ÌýÌýÌý x backfills completed for number of backfills completed, and
ÌýÌýÌý Off in case no backfills are configured.
Connection panel
When no dataset is selected in the datasets table, a panel on the right side of the Connections interface shows connection options and details.
The status of importing new data for datasets:
ÌýÌýÌý x On for how many datasets are configured to import new data, and
ÌýÌýÌý x Off for how many datasets new data import is turned off.
The status of backfill data for datasets.
ÌýÌýÌý x backfills failed for number of failed backfills across datasets,
ÌýÌýÌý x backfills processing for number of processing backfills across datasets,
ÌýÌýÌý x backfills completed for number of completed backfills for datasets, and
ÌýÌýÌý Off in case no backfills are defined for the datasets in the connection.
The transformation status of applicable B2B lookup datasets. See Transform datasets for B2B lookups for more information.
ÌýÌýÌý x On for number of datasets enabled for transformation.
Dataset panel
When a dataset is selected in the datasets table, a panel on the right side of the Connections interface show details for the selected dataset.
How many rows were skipped during ingestion in the selected time period.
Reasons for skipping records include: Missing timestamps, missing or invalid person ID, and so forth. Updated every 10 minutes.
Invalid person IDs (such as undefined
, or 00000000
, or any combination of numbers and letters in a Person ID that appears in an event more than 1 million times in a given month) are IDs that cannot be attributed to any specific user or person. These rows cannot be ingested into the system and result in error-prone ingestion and reporting. To fix invalid person IDs, you have 3 options:
- Use Stitching to populate the undefined or all-zero user IDs with valid user IDs.
- Blank out the user ID, which is then skipped during ingestion (preferable to invalid or all-zero user IDs).
- Fix any invalid user IDs in your system before ingesting the data.
The status of importing new data for the dataset:
ÌýÌýÌý x On if the dataset is configured to import new data, and
ÌýÌýÌý x Off if the dataset is configured not to import new data.
The status of backfill data for the dataset.
ÌýÌýÌý x backfills failed for number of failed backfills,
ÌýÌýÌý x backfills processing for number of processing backfills,
ÌýÌýÌý x backfills completed for number of backfills completed, and
ÌýÌýÌý Off in case no backfills are configured.
To show a dialog with an overview of the past backfills for the dataset, select {width="15"} Past backfills.
Usage connections-usage
The Usage interface shows the usage of ingested and reportable rows across all connections. If not selected, select the Usage tab to access the interface.
This interface supports you to determine whether your Customer Journey Analytics usage complies with what is contractually agreed upon. In addition to monitoring purposes, you can use the Usage interface to plan your Customer Journey Analytics license renewal.
The Usage interface uses the folowing metrics
The Usage interface consists of two panels:
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The Key usage metrics panel: provides core and historical data reportable rows. The panel also tracks percentage changes compared to the previous month for both core and historical data rows.
The panel displays in a visualization:
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Core data reportable rows.
How many reportable rows do you have over the last 13 months. The summary number is the number of core reportable rows (for example, 741M) for the last month (for example, December 2024).
-
Historical data reportable rows.
How many reportable rows do you have for the period older than 13 months. The summary number is the number of historical reportable rows (for example, 127M) for the last month (for example, December 2024).
When you hover over any stacked bar in the visualization, a popup shows the number of rows for that specific part of the bar (for example).
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-
A combined panel, showing three subpanels for:
accordion Ingested rows The Ingested rows subpanel measures the total number of records added to the system each month, providing insight into data growth and ingestion rates. The subpanel provides a summary of this month’s total ingested rows and the change from the previous month.
You can hover over data points in the visualization to display a popup with more details.
accordion Reportable rows The Reportable rows visualization tracks the number of rows available for reporting by subtracting skipped and deleted rows from ingested rows, serving as a key metric for billing and data usage. The subpanel provides two summaries:
- Last month total: A summary of total reportable rows up until this month.
- This month: A summary of this month’s total reportable rows and the change from the previous month.
You can hover over data points in the visualizations to display a popup with more details.
accordion Detail breakdown You can use the Detail breakdown table to view detailed metrics by connection, dataset, sandbox, and tags. Datasets are reported using ids instead of names, as dataset names can be modified during a reporting period. Unknown datasets or connections are reported using ids.
For the months before September 2024, data was collected at the dataset level and is displayed as Other datasets for clarity. Starting from September 2024, data is gathered at a granular dataset level, and Other datasets does no longer appear.
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To change the breakdown, select a combination for View by and Breakdown by.
table 0-row-2 1-row-2 2-row-2 3-row-2 4-row-2 View by options Breakdown by options Connection - and Dataset Dataset - Sandbox Connection Tag Connection
You can define a Time range in months to report on. Use to select the time range.