Create or edit a connection create-or-edit-a-connection
The connection creation and edit workflow experience brings all the dataset and connection configuration settings to the center of the screen with an assistive workflow. It provides detailed dataset selection, configuration, and review experience. And allows you to specify critical information like dataset type, size, schema, dataset id, batch status, backfill status, identities, and much more, to reduce the risk of wrong connection configuration. Here is an overview of the capabilities:
- You can enable a rolling data retention window when you create the connection.
- You can add to and remove datasets from a connection. (Removing a dataset removes it from the connection and impacts any associated data views and underlying Analysis Workspace projects.)
- You can enable and request backfill data per dataset.
- You can edit datasets, for example to request another backfill.
- You can import existing data per dataset.
See
Prerequisites
The maximum number of datasets you can add to a connection is capped at 100. The mix depends on which Customer Journey Analytics package your company has purchased.
Contact your administrator if you鈥檙e unsure which Customer Journey Analytics package you have.
Create a connection create-connection
To create a connection:
- In Customer Journey Analytics, select Connections, optionally from Data management, in the top menu.
- Select Create new connection.
You can now edit the details for your connection.
Edit a connection edit-connection
How you edit the connection depends on the Customer Journey Analytics package you have licensed:
Customer Journey Analytics
In the Connections > Name of the connection screen:
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Configure the connection settings.
table 0-row-2 1-row-2 2-row-2 3-row-2 4-row-2 5-row-2 6-row-2 Setting Description Connection name Enter a unique name for the connection. Connection description Describe the purpose of this connection. Tags Specify tags to add tags to your connection so you can use these tags to search for the connection at a later stage. Enable rolling data window 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 蜜豆视频 Experience Platform data retention setting supersedes the retention period. If you have 25 months鈥 worth of data in Experience Platform, Customer Journey Analytics gets 25 months of data through backfill. If you deleted 10 of those months in Experience Platform, Customer Journey Analytics would retain the remaining 15 months.
- If you enable a rolling data window, specify in Select number of months the number of months for which you enable the rolling data window.
Sandbox Choose a sandbox in Experience Platform that contains the datasets for which you want to create a connection.
蜜豆视频 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 鈥渄ata silos鈥 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.
Add datasets Select 
For the datasets you have configured, the table of datasets shows the following columns:
table 0-row-2 1-row-2 2-row-2 3-row-2 4-row-2 5-row-2 6-row-2 7-row-2 8-row-2 9-row-2 10-row-2 11-row-2 12-row-2 13-row-2 Column Description Dataset name 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
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Last updated For event datasets only, this setting is automatically set to the default timestamp field from event-based schemas in Experience Platform. 鈥淣/A鈥 means that this dataset contains no data. Number of records The total records in the previous month for the dataset in Experience Platform. Schema The schema based on which the dataset was created in 蜜豆视频 Experience Platform. Dataset type For each dataset that you added to this connection, Customer Journey Analytics automatically sets the dataset type based on the data coming in. There are 3 different dataset types: Event data, Profile data, and Lookup data. See the table below for an explanation of dataset types. Granularity The granularity of the data in the dataset; only applicable for summary datasets. Data source type The data source type of the dataset. Not applicable for summary datasets. Person ID The Person ID that is used to support person-based reporting for the dataset. Key The key that is used for a lookup dataset. Matching Key The matching key that is used for a lookup dataset. Import new data The status of importing new data for the dataset:
Backfill data The status of backfill data for the dataset.
You can search for a specific dataset using the
Customer Journey Analytics B2B Edition
[B2B Edition]{class="badge informative" title="Customer Journey Analytics B2B Edition"}
In the Connections > Name of the connection screen:
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Configure the connection settings.
table 0-row-2 1-row-2 2-row-2 3-row-2 4-row-2 5-row-2 6-row-2 7-row-2 8-row-2 Setting Description Connection name Enter a unique name for the connection. Connection description Describe the purpose of this connection. Tags Specify tags to add tags to your connection so you can use these tags to search for the connection at a later stage. Primary ID Select the proper primary ID for your connection:
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As soon as you add one or more datasets to your connection, you are no longer able to change the primary ID.
The selection of the primary ID defines whether the connection is person based or account based. The connection base determines the available settings for certain types of datasets.Optional containers If you have selected
- Global account: enables configuration of global accounts in a connection.
- Opportunity: enables configuration of opportunities in a connection.
- Buying group: enables configuration of buying groups in a connection.
Sandbox Choose a sandbox in Experience Platform that contains the datasets to which you want to create a connection.
蜜豆视频 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 鈥渄ata silos鈥 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.
Enable rolling data window 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 蜜豆视频 Experience Platform data retention setting supersedes the retention period. If you have 25 months鈥 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.
- If you enable a rolling data window, specify in Select number of months the number of months for which you enable the rolling data window.
Add datasets Select For the datasets you have configured, the table of datasets shows the following columns:
table 0-row-2 1-row-2 2-row-2 3-row-2 4-row-2 5-row-2 6-row-2 7-row-2 8-row-2 9-row-2 10-row-2 11-row-2 12-row-2 13-row-2 14-row-2 15-row-2 16-row-2 17-row-2 Column Description Dataset name 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
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Last updated For event datasets only, this setting is automatically set to the default timestamp field from event-based schemas in Experience Platform. 鈥淣/A鈥 means that this dataset contains no data. Number of records The total records in the previous month for the dataset in Experience Platform. Schema The schema based on which the dataset was created in 蜜豆视频 Experience Platform. Dataset type For each dataset that you added to this connection, Customer Journey Analytics automatically sets the dataset type based on the data coming in. There are 3 different dataset types: Event data, Profile data, and Lookup data. See the table below for an explanation of dataset types. Granularity The granularity of the data in the dataset; only applicable for summary datasets. Data source type The data source type of the dataset. Not applicable for summary datasets. Account ID (only displayed for account based connections) The Account ID that is used to support account-based reporting for the dataset. Global Account ID (only displayed for account based connections) The global Account ID that is used to support account-based reporting for the dataset. Buying Group ID (only displayed for account based connections) The Buying Group ID that is used to lookup buying group data. Opportunity ID (only displayed for account based connections) The Opportunity ID that is used to lookup opportunity data. Person ID The Person ID that is used to support person-based reporting for the dataset. Key The key that is used for a lookup dataset. Matching Key The matching key that is used for a lookup dataset. Import new data The status of importing new data for the dataset:
Backfill data The status of backfill data for the dataset.
You can search for a specific dataset using the
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Datasets datasets
You add one or more datasets or edit existing datasets as part of connection workflow.
Add datasets
You can add one or more Experience Platform datasets when you create or edit a connection.
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In Connection > Name of the connection interface, select
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In the 鉃 Select datasets step, you see a list of the Experience Platform datasets.
For each dataset, the list shows:
table 0-row-2 1-row-2 2-row-2 3-row-2 4-row-2 5-row-2 6-row-2 7-row-2 Column Description Dataset Name of the dataset. Select the name to direct you to the dataset in Experience Platform. Select 
Dataset type The type of dataset: Event, Profile, Lookup, or Summary. Number of records The total records in the previous month for the dataset in Experience Platform. Schema The schema for the dataset. Select the name to direct you to the schema in Experience Platform. Last batch The state of the last batch ingested in Experience Platform. See Batch states more information. Dataset ID The id of the dataset. Last updated The last updated timestamp of the dataset. - To change the columns displayed for the list of datasets, select
- To search for a specific dataset, use the
- To toggle between showing or hiding the selected datasets, select
- To remove a dataset from the list of selected datasets, use
- To display details of a dataset, select
- To change the columns displayed for the list of datasets, select
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Select one or more datasets and select Next. At least one event dataset must be part of the connection.
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Configure the settings for each of the selected datasets, one by one, in the 鉃 Datasets settings step of the Add datasets dialog.
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Select Add datasets to add the configured datasets to the connection. You are notified when you have not provided all required settings for each of the datasets you want to add.
Alternatively, you can select Cancel to cancel the addition of datasets to the connection. Or select Back to step back to the 鉃 Select datasets step.
Edit a dataset
To edit a dataset that is already configured for a connection, in the Connections > Name of the connection interface:
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Select
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Select
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Configure the dataset settings in the Edit dataset: Dataset name dialog.
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Select Apply to apply the dataset settings. Select Cancel to cancel.
Dataset settings
When you add datasets or edit an existing dataset, you configure the dataset settings for each dataset. The settings available depend on the type of dataset and, for some dataset types, on the type of connection (person based or[B2B Edition]{class="badge informative" title="Customer Journey Analytics B2B Edition"} account based.).
All datasets and dataset types have general settings and details, such as whether or not to import new data and request backfills.
Event dataset
The specific settings for an event dataset are dependent on the type of connection.
Person based connection
For an event dataset in a person based connection, you can specify:
Select a Person ID from the drop-down list of available identities. These identities were defined in the dataset schema in Experience Platform. See Use Identity Map as a Person ID for information on how to use Identity Map as a Person ID.
If there are no Person IDs to choose from, that means no Person IDs are 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.
Account based connection
[B2B Edition]{class="badge informative" title="Customer Journey Analytics B2B Edition"}
For an event dataset in an account based connection, you can specify:
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 Use Identity Map as a Person ID 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.
Profile dataset
The specific settings for a profile dataset are dependent on the type of connection.
Person based connection
For a profile dataset in a person based connection, you specify:
Select a Person ID from the drop-down list of available identities. These identities were defined in the dataset schema in Experience Platform. See Use Identity Map as a Person ID for information on how to use Identity Map as a Person ID.
If there are no Person IDs to choose from, that means no 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.
Account based connection
For a profile dataset in an account based connection, you specify:
Select a Person ID from the drop-down list of available identities. These identities were defined in the dataset schema in Experience Platform. See Use Identity Map as a Person ID for information on how to use Identity Map as a Person ID.
If there are no Person IDs to choose from, that means no 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.
Lookup dataset
The specific settings for a lookup dataset are dependent on the type of connection.
Person based connection
For a lookup dataset in a person based connection, you specify:
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.
Account based connection
[B2B Edition]{class="badge informative" title="Customer Journey Analytics B2B Edition"}
For a lookup dataset in an account based connection, you can specify:
The matching key to join on in one of the event datasets. If this list is empty, you probably haven鈥檛 added or configured an event dataset.
Based on your selected Matching key type, select the appropriate value:
- Match by field:
Select a field from the Matching key dropdown menu to join with one of the event datasets. If this list is empty, you probably haven鈥檛 added or configured an event dataset. - Match by container:
Select a container from the Matching key dropdown menu to use to join with one of the event datasets. The containers you included as part of setting up the connection determine the available containers to select. If this list is empty, you probably haven鈥檛 configured one or more containers.
Summary dataset
The specific settings for a summary dataset are:
General dataset settings and details
Each (type of dataset) has the following common settings:
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.
- Define the period by entering start and end data or selecting dates using
- Select Queue backfill to add the backfill to the list, or Cancel to cancel.
For each entry, select
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
Delete a dataset
When you delete a dataset, you are notified about the implications of the deletion. Deletion of a dataset can impact all associated connections, data views and projects. Also, if you do delete the one and only event or summary dataset in your connection, you are prompted to add another event or summary dataset. You can only save a connection that contains at least one event or summary dataset.
Past backfills
When you select
Connection preview preview
To preview the connection that you have created, select
This preview contains some columns listing the connection configuration. What column types are shown depends on your individual datasets.
Connection map
[B2B Edition]{class="badge informative" title="Customer Journey Analytics B2B Edition"}
To see a map of the relationships between the datasets that are part of your connection, select
This map helps you to get a better understanding of how you have defined your connection and set up the relationship between your event, profile, lookup, and summary data datasets using identifiers.
Dataset types dataset-types
For each dataset that you add to this connection, Customer Journey Analytics automatically sets the dataset type based on the data coming in.
There are different dataset types: Event data, Profile data, Lookup data and Summary data.
Use numeric fields as lookup keys and lookup values numeric
This lookup functionality is useful if you want to add a numeric field such as a cost or margin to a string-based key field. It allows numeric values to be part of lookups, either as keys or as values. In your lookup schema, you might have numeric values tied to, for example, your product names, COGS, campaign marketing cost, or margins. Here is an example lookup schema in 蜜豆视频 Experience Platform:
You now support bringing in these values as metrics or dimensions into Customer Journey Analytics reporting. When you set up your connection and pull in lookup datasets, you can edit the datasets to select the Key and Matching Key:
When you set up a data view based on this connection, you add the numeric values as components to the data view. Any project based on this data view can then report on these numeric values.
Use Identity Map as a Person ID id-map
Customer Journey Analytics supports the ability to use the Identity Map for its Person ID. Identity Map is a map data structure that allows you to upload key value pairs. The keys are identity namespaces and the value is a structure that holds the identity value. The Identity Map exists on each row/event uploaded and is populated for each row accordingly.
The Identity Map is available for any dataset that uses a schema based on the ExperienceEvent XDM class. When you select such a dataset to be included in a Customer Journey Analytics Connection, you have the option of selecting either a field as the primary ID or the Identity Map:
If you select Identity Map, you get two additional configuration options:
primary=true attribute and use that identity as the Person ID for that row. This identity is the primary key that is used in Experience Platform for partitioning. And this identity is also the prime candidate for usage as Customer Journey Analytics Person ID (depending on how the dataset is configured in a Customer Journey Analytics connection).Identity Map edge cases id-map-edge
This table shows the two configuration options when edge cases are present and how they are handled:
Calculate the average number of daily events average-number
This calculation is done for every dataset in the connection.
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Go to 蜜豆视频 Experience Platform Query Services and create a query.
The query would look like this:
code language-none 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;In this example, 鈥渁nalytics_demo_data鈥 is the name of the dataset.
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To show all the datasets that exist in 蜜豆视频 Experience Platform, perform the
Show Tablesquery.
Algorithmic pruning of large lookup datasets
When creating a connection, you can add large datasets for lookup purposes. For example, a dataset representing a product catalog so descriptive product information can be looked up when building reports and visualizations. Such a large lookup dataset can exceed the maximum of 10 million unique lookups currently implemented as a guardrail, resulting in additional data being skipped.
You can request an algorithmic pruning of a large lookup dataset. This algorithmic pruning only keeps data in the lookup dataset that matches the keys in your event dataset. This way, you don鈥檛 need to load the entire unpruned lookup dataset. Old or less frequently used items are removed, which might slightly affect reports but brings significant benefits. The algorithm looks back 90 days and updates weekly.
Contact your 蜜豆视频 support team for further information and to enable this capability.
