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| Certification Vendor: | Salesforce |
|---|---|
| Exam Name: | Salesforce Certified Data 360 Consultant |
| Exam Number: | Data-Con-101 |
| Real Exam Qty: | 60 |
| Available Languages: | English |
| Exam Price: | $200 USD |
| Certificate Validity Period: | 3 years |
| Exam Format: | Multiple Select, Multiple Choice |
| Exam Duration: | 90 minutes |
| Related Certifications: | Salesforce Certified Administrator Salesforce Certified Data Architect |
| Passing Score: | 63% |
| Sample Questions: | Salesforce Data-Cloud-Consultant Sample Questions |
| Exam Way: | Online proctored exam |
| Pre Condition: | Recommended: Salesforce Administrator certification and hands-on experience with Data Cloud implementation |
| Official Syllabus URL: | https://trailhead.salesforce.com/credentials/data360consultant |
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NEW QUESTION # 51
A Data Cloud consultant is evaluating the initial phase of the Data Cloud lifecycle for a company.
Which action is essential to effectively begin the Data Cloud lifecycle?
Answer: A
Explanation:
* Data Cloud Lifecycle: The initial phase of the Salesforce Data Cloud lifecycle is critical for setting the foundation for successful data integration and utilization.
* Identifying Use Cases:
Importance: Defining clear use cases helps in understanding the business objectives and how Data Cloud can address them.
Required Data Sources: Identifying the necessary data sources ensures that relevant data is ingested into Data Cloud.
Data Quality: Assessing data quality is essential for accurate and reliable data analysis and insights.
* Actions:
Step 1: Engage with stakeholders to define specific use cases for Data Cloud.
Step 2: Identify and catalog the required data sources for these use cases.
Step 3: Evaluate the quality of data from these sources to ensure they meet the standards for effective data analysis.
* Reference:
Salesforce Data Cloud Implementation Guide
Salesforce Data Cloud Lifecycle
NEW QUESTION # 52
Which information is provided in a .csv file when activating to Amazon S3?
Answer: A
Explanation:
Explanation
When activating to Amazon S3, the information that is provided in a .csv file is the activated data payload. The activated data payload is the data that is sent from Data Cloud to theactivation target, which in this case is an Amazon S3 bucket1. The activated data payload contains the attributes and values of the individuals or entities that are included in the segment that is being activated2. The activated data payload can be used for various purposes, such as marketing, sales, service, or analytics3. The other options are incorrect because they are not provided in a .csv file when activating to Amazon S3. Option A is incorrect because an audit log is not provided in a .csv file, but it can be viewed in the Data Cloud UI under the Activation History tab4. Option C is incorrect because the metadata regarding the segment definition is not provided in a .csv file, but it can be viewed in the Data Cloud UI under the Segmentation tab5. Option D is incorrect because the manifest of origin sources within Data Cloud is not provided in a .csv file, but it can be viewed in the Data Cloud UI under the Data Sources tab. References: Data Activation Overview, Create and Activate Segments in Data Cloud, Data Activation Use Cases, View Activation History, Segmentation Overview, [Data Sources Overview]
NEW QUESTION # 53
A Data 360 Consultant has successfully ingested and mapped a custom schema for " Vehicle Insurance Policies " into a custom data model object (DMO) named Insurance_Policy__c. However, when a marketer attempts to create a new segment on the Individual object, the Insurance_Policy__c object is not accessible in Segment Builder.
What is the most likely reason for this behavior?
Answer: A
Explanation:
Segment Builder exposes attributes according to the relationships that exist between the object being segmented and other DMOs in the Data 360 data model. If Insurance_Policy__c has no relationship path to the Individual DMO, Segment Builder cannot traverse from Individual to the insurance-policy records, so the DMO will not appear as an available related object. Salesforce documents that relationship cardinality determines whether a DMO appears as a direct or related attribute: 1:1 and N:1 relationships typically surface as direct attributes, while 1:N relationships surface as related attributes. Consequently, the mere existence and successful mapping of a custom DMO is insufficient. Value Suggestions affect convenient value selection, not DMO visibility, and there is no generic "enable for segmentation" switch that resolves a missing relationship.
NEW QUESTION # 54
A consultant is building a segment to announce a new product launch for customers that have previously purchased black pants.
How should the consultant place attributes for product color and product type from the Order Product object to meet this criteria?
Answer: B
Explanation:
To create a segment based on the product color and product type from the Order Product object, the consultant should place the attributes for product color and product type in a single container. This way, the segment will include only the customers who have purchased black pants, and not those who have purchased black shirts or blue pants. A container is a grouping of attributes that defines a segment of individuals based on a logical AND operation. Placing the attributes in separate containers would result in a segment that includes customers who have purchased any black product or any pants product, which is not the desired criteria. Placing an attribute for the "black" calculated insight would not work, because calculated insights are based on aggregated data and not individual-level data. Placing the attributes as direct attributes would not work, because direct attributes are used to filter individuals based on their profile data, not their order data. Reference:
Create a Segment in Data Cloud
Learn About Segmentation Tools
Salesforce Launches: Data Cloud Consultant Certification
NEW QUESTION # 55
A consultant wants to make sure address details from customer orders are selected as best to save to the unified profile.
What should the consultant do to achieve this?
Answer: C
Explanation:
* Unified Profile: Creating a unified customer profile in Salesforce Data Cloud involves consolidating data from various sources.
* Reconciliation Rules: These rules determine which data source is considered the "best" when conflicting data is encountered. Changing reconciliation rules allows prioritizing specific sources.
* Source Priority: Setting source priority involves defining which data source should be preferred over others for specific attributes.
* Process:
Step 1: Access the Data Cloud settings for reconciliation rules.
Step 2: Select the Contact Point Address details.
Step 3: Change the reconciliation rules for address attributes to "Source Priority." Step 4: Move the Order DMO to the top of the priority list. This ensures that address details from customer orders are prioritized and selected as the best data to save to the unified profile.
* Benefits:
Accuracy: Ensures the most accurate and reliable address data is used in the unified profile.
Relevance: Gives priority to the most relevant and frequently updated source (customer orders).
* Reference:
Salesforce Data Cloud Reconciliation Rules
Salesforce Unified Customer Profile
NEW QUESTION # 56
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