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| Certification Vendor: | Salesforce |
|---|---|
| Exam Name: | Salesforce Certified Data Cloud Consultant Exam |
| Exam Number: | Data-Con-101 |
| Exam Format: | Multiple-choice, Multiple-select |
| Passing Score: | 62% |
| Exam Price: | USD 200 (+ applicable taxes) |
| Related Certifications: | Salesforce Certified Consultant |
| Exam Duration: | 105 minutes |
| Real Exam Qty: | 60–65 (including up to 5 unscored items) |
| Available Languages: | English |
| Certificate Validity Period: | 2 years |
| Recommended Training: | Cert Prep: Salesforce Certified Data Cloud Consultant Trailhead: Data Cloud Fundamentals (SDC101) |
| Exam Registration: | Pearson VUE Kryterion Webassessor |
| Sample Questions: | Salesforce Data-Con-101 Sample Questions |
| Exam Way: | Online proctored or onsite testing center |
| Pre Condition: | No mandatory prerequisites; recommended 2+ years experience in data strategy, modeling, and Salesforce implementation |
| Official Syllabus URL: | https://trailheadacademy.salesforce.com/certificate/exam-data-cloud---Data-Con-101 |
>> Valid Salesforce Data-Con-101 Test Cost <<
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NEW QUESTION # 159
Northern Trail Outfitters (NTO) is getting ready to start ingesting its CRM data into Data Cloud.
While setting up the connector, which type of refresh should NTO expect when the data stream is deployed for the first time?
Answer: C
Explanation:
Data Stream Deployment: When setting up a data stream in Salesforce Data Cloud, the initial deployment requires a comprehensive data load.
Types of Refreshes:
Incremental Refresh: Only updates with new or changed data since the last refresh.
Manual Refresh: Requires a user to manually initiate the data load.
Partial Refresh: Only a subset of the data is refreshed.
Full Refresh: Loads the entire dataset into the system.
First-Time Deployment: For the initial deployment of a data stream, a full refresh is necessary to ensure all data from the source system is ingested into Salesforce Data Cloud.
References:
Salesforce Documentation: Data Stream Setup
Salesforce Data Cloud Guide
NEW QUESTION # 160
Cumulus Financial created a segment called High Investment Balance Customers. This is a foundational segment that includes several segmentation criteria the marketing team should consistently use.
Which feature should the consultant suggest the marketing team use to ensure this consistency when creating future, more refined segments?
Answer: D
Explanation:
Nested segments are segments that include or exclude one or more existing segments. They allow the marketing team to reuse filters and maintain consistency in their data by using an existing segment to build a new one. For example, the marketing team can create a nested segment that includes High Investment Balance Customers and excludes customers who have opted out of email marketing. This way, they can leverage the foundational segment and apply additional criteria without duplicating the rules. The other options are not the best features to ensure consistency because:
B). A calculated insight is a data object that performs calculations on data lake objects or CRM data and returns a result. It is not a segment and cannot be used for activation or personalization.
C). A data kit is a bundle of packageable metadata that can be exported and imported across Data Cloud orgs.
It is not a feature for creating segments, but rather for sharing components.
D). Cloning a segment creates a copy of the segment with the same rules and filters. It does not allow the marketing team to add or remove criteria from the original segment, and it may create confusion and redundancy. References: Create a Nested Segment - Salesforce, Save Time with Nested Segments (Generally Available) - Salesforce, Calculated Insights - Salesforce, Create and Publish a Data Kit Unit | Salesforce Trailhead, Create a Segment in Data Cloud - Salesforce
NEW QUESTION # 161
A consultant wants to build a new audience in Data Cloud.
Which three criteria can the consultant include when building a segment?
Choose 3 answers
Answer: A,B,E
Explanation:
A segment is a subset of individuals who meet certain criteria based on their attributes and behaviors. A consultant can use different types of criteria when building a segment in Data Cloud, such as:
Direct attributes: These are attributes that describe the characteristics of an individual, such as name, email, gender, age, etc. These attributes are stored in the Profile data model object (DMO) and can be used to filter individuals based on their profile data.
Calculated Insights: These are insights that perform calculations on data in a data space and store the results in a data extension. These insights can be used to segment individuals based on metrics or scores derived from their data, such as customer lifetime value, churn risk, loyalty tier, etc.
Related attributes: These are attributes that describe the relationships of an individual with other DMOs, such as Email, Engagement, Order, Product, etc. These attributes can be used to segment individuals based on their interactions or transactions with different entities, such as email opens, clicks, purchases, etc.
The other two options are not valid criteria for building a segment in Data Cloud. Data stream attributes are attributes that describe the streaming data that is ingested into Data Cloud from various sources, such as Marketing Cloud, Commerce Cloud, Service Cloud, etc. These attributes are not directly available for segmentation, but they can be transformed and stored in data extensions using streaming data transforms.
Streaming insights are insights that analyze streaming data in real time and trigger actions based on predefined conditions. These insights are not used for segmentation, but for activation and personalization. References: Create a Segment in Data Cloud, Use Insights in Data Cloud, Data Cloud Data Model
NEW QUESTION # 162
A consultant is troubleshooting a segment error.
Which error message is solved by using calculated insights Instead of nested segments?
Answer: C
Explanation:
Segment Errors in Data Cloud: Segments in Salesforce Data Cloud can encounter errors due to various reasons, including complexity and nested segments.
Calculated Insights vs. Nested Segments:
Complex Segments: If a segment is too complex due to extensive nesting or numerous conditions, it can lead to errors.
Simplification with Calculated Insights: Using calculated insights can simplify segment creation by pre- computing and storing complex logic or aggregations, which can then be referenced directly in the segment.
Solution:
Step 1: Identify the segment causing the "Segment is too complex" error.
Step 2: Break down complex logic into calculated insights.
Step 3: Use these calculated insights in segment definitions to reduce complexity.
References:
Salesforce Data Cloud Calculated Insights
Salesforce Data Cloud Segment Creation
NEW QUESTION # 163
What is the result of a segmentation criteria filtering on City | Is Equal To | 'San Jose'?
Answer: C
Explanation:
The result of a segmentation criteria filtering on City | Is Equal To | 'San Jose' is cities only containing 'San Jose' or 'san jose'. This is because the segmentation criteria is case-sensitive and accent-sensitive, meaning that it will only match the exact value that is entered in the filter1. Therefore, cities containing 'San Jose', 'san jose', or 'San Jose' will not be included in the result, as they do not match the filter value exactly. To include cities with different variations of the name 'San Jose', you would need to use the OR operator and add multiple filter values, such as 'San Jose' OR 'San Jose' OR 'san jose' OR 'san jose'
2. References: Segmentation Criteria, Segmentation Operators
NEW QUESTION # 164
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