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Salesforce Data-Cloud-Consultant Exam Syllabus Topics:
Topic
Details
Topic 1
- Identity Resolution: It describes matching and how its rule sets are applied. Furthermore, it discusses reconciling data and its rule sets, the results of identity resolution, and use cases.
Topic 2
- Data Ingestion and Modeling: This topic covers the different transformation capabilities within Data Cloud. It includes describing processes and considerations for data ingestion from various sources, defining, mapping, and modeling data using best practices aligned with identity resolution. Lastly, it discusses using available tools to inspect and validate ingested and modeled data.
Topic 3
- Segmentation and Insights: This topic defines basic concepts of segmentation and use cases, identifies scenarios for analyzing segment membership, configuring, refining, and maintaining segments within Data Cloud, and differentiating between calculated and streaming insights.
Topic 4
- Data Cloud Overview: This topic covers Data Cloud's function, key terminology, business value, typical use cases, the Data Cloud lifecycle, dependencies, and principles of data ethics. These sub-topics provide an overview of Data Cloud's capabilities and applications.
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Salesforce Certified Data Cloud Consultant Sample Questions (Q69-Q74):
NEW QUESTION # 69
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. Identity resolution rules have been added to the ruleset to increase the number of matched profiles.
- B. New data sources have been added to Data Cloud that largely overlap with the existing profiles.
- C. Identity resolution rules have been removed to reduce the number of matched profiles.
- D. Duplicates have been removed from source system data streams.
Answer: A,B
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.
References: Identity Resolution Calculated Insight: Consolidation Rates for Unified Profiles, Configure Identity Resolution Rulesets
NEW QUESTION # 70
Northern Trail Outfitters (NTO) wants to send a promotional campaign for customers that have purchased within the past 6 months. The consultant created a segment to meet this requirement.
Now, NTO brings an additional requirement to suppress customers who have made purchases within the last week.
What should the consultant use to remove the recent customers?
- A. Batch transforms
- B. Streaming insight
- C. Related attributes
- D. Segmentation exclude rules
Answer: D
Explanation:
The consultant should use B. Segmentation exclude rules to remove the recent customers. Segmentation exclude rules are filters that can be applied to a segment to exclude records that meet certain criteria. The consultant can use segmentation exclude rules to exclude customers who have made purchases within the last week from the segment that contains customers who have purchased within the past 6 months. This way, the segment will only include customers who are eligible for the promotional campaign.
The other options are not correct. Option A is incorrect because batch transforms are data processing tasks that can be applied to data streams or data lake objects to modify or enrich the data. Batch transforms are not used for segmentation or activation. Option C is incorrect because related attributes are attributes that are derived from the relationships between data model objects. Related attributes are not used for excluding records from a segment. Option D is incorrect because streaming insights are derived attributes that are calculated at the time of data ingestion. Streaming insights are not used for excluding records from a segment. References: Salesforce Data Cloud Consultant Exam Guide, Segmentation, Segmentation Exclude Rules
NEW QUESTION # 71
A customer has a custom Customer Email c object related to the standard Contact object in Salesforce CRM.
This custom object
stores the email addressa Contact that they want to use for activation.
To which data entity ismapped?
- A. Custom customer Email__c object
- B. Contact Point_Email
- C. Contact
- D. Individual
Answer: B
Explanation:
Explanation
The Contact Point_Email object is the data entity that represents an email address associated with an individual in Data Cloud. It is part of the Customer 360 Data Model, which is a standardized data model that defines common entities and relationships for customer data. The Contact Point_Email object can be mapped to any custom or standard object that stores email addresses in Salesforce CRM, such as the custom Customer Email__c object. The other options are not the correct data entities to map to because:
* A. The Contact object is the data entity that represents a person who is associated with an account that is a customer, partner, or competitor in Salesforce CRM. It is not the data entity that represents an email address in Data Cloud.
* C. The custom Customer Email__c object is not a data entity in Data Cloud, but a custom object in Salesforce CRM. It can be mapped to a data entity in Data Cloud, such as the Contact Point_Email object, but it is not a data entity itself.
* D. The Individual object is the data entity that represents a unique person in Data Cloud. It is the core entity for managing consent and privacy preferences, and it can be related to one or more contact points, such as email addresses, phone numbers, or social media handles. It is not the data entity that represents an email address in Data Cloud. References: Customer 360 Data Model: Individual and Contact Points - Salesforce, Contact Point_Email | Object Reference for the Salesforce Platform | Salesforce Developers,
[Contact | Object Reference for the Salesforce Platform | Salesforce Developers], [Individual | Object Reference for the Salesforce Platform | Salesforce Developers]
NEW QUESTION # 72
A customer notices that their consolidation rate is low across their account unification. They have mapped Account to the Individual and Contact Point Email DMOs.
What should they do to increase their consolidation rate?
- A. Update their account address details in the data source
- B. Disable the individual identity ruleset.
- C. Change reconciliation rules to Most Occurring.
- D. Increase the number of matching rules.
Answer: D
Explanation:
* Consolidation Rate: The consolidation rate in Salesforce Data Cloud refers to the effectiveness of unifying records into a single profile. A low consolidation rate indicates that many records are not being successfully unified.
* Matching Rules: Matching rules are critical in the identity resolution process. They define the criteria for identifying and merging duplicate records.
* Solution:
Increase Matching Rules: Adding more matching rules improves the system's ability to identify duplicate records. This includes matching on additional fields or using more sophisticated matching algorithms.
Steps:
Access the Identity Resolution settings in Data Cloud.
Review the current matching rules.
Add new rules that consider more fields such as phone number, address, or other unique identifiers.
* Benefits:
Improved Unification: Higher accuracy in matching and merging records, leading to a higher consolidation rate.
Comprehensive Profiles: Enhanced customer profiles with consolidated data from multiple sources.
* Reference:
Salesforce Data Cloud Identity Resolution
Salesforce Help: Matching Rules
NEW QUESTION # 73
A consultant needs to minimize the difference between a Data Cloud segment population and Marketing Cloud data extension count to determine the true size of segments for campaign planning.
What should the consultant recommend to filter the segments by to accomplish this?
- A. Business units
- B. User preferences for marketing outreach
- C. Marketing Cloud Journeys
- D. Geographical divisions
Answer: B
Explanation:
Segment Population vs. Data Extension Count: Minimizing the difference between Data Cloud segment populations and Marketing Cloud data extensions ensures accurate segment sizes for campaign planning.
Filtering by User Preferences: By filtering segments based on user preferences for marketing outreach, you ensure that only those contacts who have opted in or are eligible for marketing campaigns are included. This aligns the segment population in Data Cloud with the counts in Marketing Cloud.
Process:
* Define Preferences: Ensure that user preferences for marketing outreach are clearly defined and captured
* in the system.
* Filter Segments: Use these preferences to filter segments in Data Cloud, ensuring only the relevant contacts are included.
Benefits:
* Accuracy: Increases the accuracy of segment sizes by including only those who have opted in for marketing.
* Compliance: Helps in complying with regulatory requirements for marketing communications.
References:
* Salesforce Data Cloud Segmentation
* Marketing Cloud Data Extensions
NEW QUESTION # 74
......
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