To import campaign members into a campaign in CRM a user wants to export the segment to Amazon S3. The resulting file needs to include CRM Campaign ID in the name. How can this outcome be achieved?
A. Include campaign identifier into the activation name
B. Hard-code the campaign identifier as a new attribute in the campaign activation
C. Include campaign identifier into the filename specification
D. Include campaign identifier into the segment name
Explanation:
You can use the filename specification option in the Amazon S3 activation to customize the name of the file that is exported. You can use variables such as {campaignId} to include the CRM campaign ID in the file name.
What does the Ignore Empty Value option do in identity resolution?
A. Ignores empty fields when running any custom match rules
B. Ignores empty fields when running reconciliation rules
C. Ignores Individual object records with empty fields when running identity resolution rules
D. Ignores empty fields when running the standard match rules
Explanation:
The Ignore Empty Value option in identity resolution allows customers to ignore empty fields when running reconciliation rules. Reconciliation rules are used to determine the final value of an attribute for a unified individual profile, based on the values from different sources. The Ignore Empty Value option can be set to true or false for each attribute in a reconciliation rule. If set to true, the reconciliation rule will skip any source that has an empty value for that attribute and move on to the next source in the priority order. If set to false, the reconciliation rule will consider any source that has an empty value for that attribute as a valid source and use it to populate the attribute value for the unified individual profile.
The other options are not correct descriptions of what the Ignore Empty Value option does in identity resolution. The Ignore Empty Value option does not affect the custom match rules or the standard match rules, which are used to identify and link individuals across different sources based on their attributes. The Ignore Empty Value option also does not ignore individual object records with empty fields when running identity resolution rules, as identity resolution rules operate on the attribute level, not the record level.
Northern Trail Outfitters uploads new customer data to an Amazon S3 Bucket on a daily basis to be ingested in Data Cloud. In what order should each process be run to ensure that freshly imported data is ready and available to use for any segment?
A. Calculated Insight > Refresh Data Stream > Identity Resolution
B. Refresh Data Stream > Calculated Insight > Identity Resolution
C. Identity Resolution > Refresh Data Stream > Calculated Insight
D. Refresh Data Stream > Identity Resolution > Calculated Insight
Explanation:
To ensure that freshly imported data from an Amazon S3 Bucket is ready and available to use for any segment, the following processes should be run in this order:
Refresh Data Stream: This process updates the data lake objects in Data Cloud with the latest data from the source system. It can be configured to run automatically or manually, depending on the data stream settings. Refreshing the data stream ensures that Data Cloud has the most recent and accurate data from the Amazon S3 Bucket.
Identity Resolution: This process creates unified individual profiles by matching and consolidating source profiles from different data streams based on the identity resolution ruleset. It runs daily by default, but can be triggered manually as well. Identity resolution ensures that Data Cloud has a single view of each customer across different data sources.
Calculated Insight: This process performs calculations on data lake objects or CRM data and returns a result as a new data object. It can be used to create metrics or measures for segmentation or analysis purposes. Calculated insights ensure that Data Cloud has the derived data that can be used for personalization or activation.
A customer is concerned that the consolidation rate displayed in the identity resolution is quite low compared to their initial estimations. Which configuration change should a consultant consider in order to increase the consolidation rate?
A. Change reconciliation rules to Most Occurring.
B. Increase the number of matching rules.
C. Include additional attributes in the existing matching rules.
D. Reduce the number of matching rules.
Explanation:
The consolidation rate is the amount by which source profiles are combined to produce unified profiles, calculated as 1 - (number of unified individuals / number of source individuals). For example, if you ingest 100 source records and create 80 unified profiles, your consolidation rate is 20%. To increase the consolidation rate, you need to increase the number of matches between source profiles, which can be done by adding more match rules. Match rules define the criteria for matching source profiles based on their attributes. By increasing the number of match rules, you can increase the chances of finding matches between source profiles and thus increase the consolidation rate. On the other hand, changing reconciliation rules, including additional attributes, or reducing the number of match rules can decrease the consolidation rate, as they can either reduce the number of matches or increase the number of unified profiles.
A consultant is ingesting a list of employees from their human resources database that they want to segment on. Which data stream category should the consultant choose when ingesting this data?
A. Profile Data
B. Contact Data
C. Other Data
D. Engagement Data
Cumulus Financial uses calculated insights to compute the total banking value per branch for its high net worth customers. In the calculated insight, "banking value" is a metric, "branch" is a dimension, and "high net worth" is a filter. What can be included as an attribute in activation?
A. "high net worth" (filter)
B. "branch" (dimension) and "banking metric)
C. "banking value" (metric)
D. "branch" (dimension)
Explanation:
According to the Salesforce Data Cloud documentation, an attribute is a dimension or a measure that can be used in activation. A dimension is a categorical variable that can be used to group or filter data, such as branch, region, or product. A measure is a numerical variable that can be used to calculate metrics, such as revenue, profit, or count. A filter is a condition that can be applied to limit the data that is used in a calculated insight, such as high net worth, age range, or gender. In this question, the calculated insight uses “banking value” as a metric, which is a measure, and “branch” as a dimension. Therefore, only “branch” can be included as an attribute in activation, since it is a dimension. The other options are either measures or filters, which are not attributes.
Which statement about Data Cloud's Web and Mobile Application Connector is true?
A. A standard schema containing event, profile, and transaction data is created at the time the connector is configured.
B. The Tenant Specific Endpoint is auto-generated in Data Cloud when setting the connector.
C. Any data streams associated with the connector will be automatically deleted upon deleting the app from Data Cloud Setup.
D. The connector schema can be updated to delete an existing field.
Where is value suggestion for attributes in segmentation enabled when creating the DMO?
A. Data Mapping
B. Data Transformation
C. Segment Setup
D. Data Stream Setup
Northern Trail Outfitters (NTO), an outdoor lifestyle clothing brand, recently started a new line of business. The new business specializes in gourmet camping food. For business reasons as well as security reasons, it's important to NTO to keep all Data Cloud data separated by brand. Which capability best supports NTO's desire to separate its data by brand?
A. Data sources for each brand
B. Data model objects for each brand
C. Data spaces for each brand
D. Data streams for each brand
A user wants to be able to create a multi-dimensional metric to identify unified individual lifetime value (LTV). Which sequence of data model object (DMO) joins is necessary within the calculated Insight to enable this calculation?
A. Unified Individual > Unified Link Individual > Sales Order
B. Unified Individual > Individual > Sales Order
C. Sales Order > Individual > Unified Individual
D. Sales Order > Unified Individual
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