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Salesforce Certified Data Cloud Consultant Sample Questions (Q10-Q15):
NEW QUESTION # 10
Which two requirements must be met for a calculated insight to appear in the segmentation canvas?
Choose 2 answers
- A. The primary key of the segmented table must be a dimension in the calculated insight.
- B. The primary key of the segmented table must be a metric in the calculated insight.
- C. The calculated insight must contain a dimension including the Individual or Unified Individual Id.
- D. The metrics of the calculated insights must only contain numeric values.
Answer: A,C
Explanation:
A calculated insight is a custom metric or measure that is derived from one or more data model objects or data lake objects in Data Cloud. A calculated insight can be used in segmentation to filter or group the data based on the calculated value. However, not all calculated insights can appear in the segmentation canvas.
There are two requirements that must be met for a calculated insight to appear in the segmentation canvas:
The calculated insight must contain a dimension including the Individual or Unified Individual Id. A dimension is a field that can be used to categorize or group the data, such as name, gender, or location.
The Individual or Unified Individual Id is a unique identifier for each individual profile in Data Cloud.
The calculated insight must include this dimension to link the calculated value to the individual profile and to enable segmentation based on the individual profile attributes.
The primary key of the segmented table must be a dimension in the calculated insight. The primary key is a field that uniquely identifies each record in a table. The segmented table is the table that contains the data that is being segmented, such as the Customer or the Order table. The calculated insight must include the primary key of the segmented table as a dimension to ensure that the calculated value is associated with the correct record in the segmented table and to avoid duplication or inconsistency in the segmentation results.
References: Create a Calculated Insight, Use Insights in Data Cloud, Segmentation
NEW QUESTION # 11
Cloud Kicks wants to be able to build a segment of customers who have visited its website within the previous
7 days.
Which filter operator on the Engagement Date field fits this use case?
- A. Last Number of Days
- B. Is Between
- C. Next Number of Days
- D. Greater than Last Number of
Answer: A
Explanation:
The filter operator Last Number of Days allows you to filter on date fields using a relative date range that specifies the number of days before today. For example, you can use this operator to filter on customers who have visited your website in the last 7 days, or the last 30 days, or any number of days you want. This operator is useful for creating dynamic segments that update automatically based on the current date12. References:
* Relative Date Filter Reference
* Create Filtered Segments
NEW QUESTION # 12
Northern Trail Outfitters has the following customer data to ingest into Data Cloud and use for segmentation.
1. Propensity to purchase
2. Has active membership
3. Work email address
Which data types should the consultant use when ingesting this data?
- A. Number, Boolean, Text
- B. Percent, Boolean, Email
- C. Percent, Number, Email
- D. Number, Text, URL
Answer: A
NEW QUESTION # 13
Which data model subject area should be used for any Organization, Individual, or Member in the Customer
360 data model?
- A. Global Account
- B. Engagement
- C. Membership
- D. Party
Answer: D
Explanation:
The data model subject area that should be used for any Organization, Individual, or Member in the Customer
360 data model is the Party subject area. The Party subject area defines the entities that are involved in any business transaction or relationship, such as customers, prospects, partners, suppliers, etc. The Party subject area contains the following data model objects (DMOs):
* Organization: A DMO that represents a legal entity or a business unit, such as a company, a department, a branch, etc.
* Individual: A DMO that represents a person, such as a customer, a contact, a user, etc.
* Member: A DMO that represents the relationship between an individual and an organization, such as an employee, a customer, a partner, etc.
The other options are not data model subject areas that should be used for any Organization, Individual, or Member in the Customer 360 data model. The Engagement subject area defines the actions that people take, such as clicks, views, purchases, etc. The Membership subject area defines the associations that people have with groups, such as loyalty programs, clubs, communities, etc. The Global Account subject area defines the hierarchical relationships between organizations, such as parent-child, subsidiary, etc.
References:
* Data Model Subject Areas
* Party Subject Area
* Customer 360 Data Model
NEW QUESTION # 14
A customer notices that their consolidation rate has recently increased. They contact the consultant to ask why.
What are two likely explanations for the increase?
Choose 2 answers
- A. New data sources have been added to Data Cloud that largely overlap with the existing profiles.
- B. Duplicates have been removed from source system data streams.
- C. Identity resolution rules have been added to the ruleset to increase the number of matchedprofiles.
- D. Identity resolution rules have been removed to reduce the number of matched profiles.
Answer: A,C
Explanation:
The consolidation rate is a metric that measures the amount by which source profiles are combined to produce unified profiles in Data Cloud, calculated as 1 - (number of unified profiles / number of source profiles). A higher consolidation rate means that more source profiles are matched and merged into fewer unified profiles, while a lower consolidation rate means that fewer source profiles are matched and more unified profiles are created. There are two likely explanations for why the consolidation rate has recently increased for a customer:
New data sources have been added to Data Cloud that largely overlap with the existing profiles. This means that the new data sources contain many profiles that are similar or identical to the profiles from the existing data sources. For example, if a customer adds a new CRM system that has the same customer records as their old CRM system, the new data source will overlap with the existing one. When Data Cloud ingests the new data source, it will use the identity resolution ruleset to match and merge the overlapping profiles into unified profiles, resulting in a higher consolidation rate.
Identity resolution rules have been added to the ruleset to increase the number of matched profiles. This means that the customer has modified their identity resolution ruleset to include more match rules or more match criteria that can identify more profiles as belonging to the same individual. For example, if a customer adds a match rule that matches profiles based on email address and phone number, instead of just email address, the ruleset will be able to match more profiles that have the same email address and phone number, resulting in a higher consolidation rate.
Identity Resolution Calculated Insight: Consolidation Rates for Unified Profiles, Configure Identity Resolution Rulesets
NEW QUESTION # 15
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