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| Certification Vendor: | Salesforce |
|---|---|
| Exam Name: | Salesforce Certified Data 360 Consultant (formerly Salesforce Certified Data Cloud Consultant) |
| Exam Number: | Data-Con-101 / Data-Cloud-Consultant |
| Real Exam Qty: | 60 (plus up to 5 unscored questions) |
| Passing Score: | 62% - 70% |
| Exam Duration: | 105 minutes |
| Related Certifications: | Salesforce Certified Marketing Cloud Consultant Salesforce Certified Data Architect Salesforce Certified Administrator |
| Exam Format: | Scenario-based questions, Multiple-choice, Multiple-select |
| Certificate Validity Period: | 3 years |
| Exam Price: | USD $200 + applicable taxes |
| Available Languages: | English |
| Recommended Training: | Salesforce Trailhead - Data 360 / Data Cloud Learning Path |
| Exam Registration: | Salesforce Webassessor Registration |
| Sample Questions: | Salesforce Data-Cloud-Consultant Sample Questions |
| Exam Way: | Online proctored or onsite at authorized testing centers |
| Pre Condition: | No mandatory prerequisites; recommended: 1–2 years experience in data management, Salesforce implementation, or CDP solutions |
| Official Syllabus URL: | https://help.salesforce.com/s/articleView?id=005298940&language=en_US |
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質問 # 41
A data architect is using Change Sets to move a new set of data configurations between two Salesforce Data
360 environments. The architect has created a data kit in the source org that includes several new data streams and identity resolution rules. Which component type should the architect select when adding these to the outbound change set to ensure the configuration is successfully transferred?
正解：B
解説：
The lifecycle point is that Data 360 configuration is metadata, but it still has product-specific packaging and activation steps. Data Package Kit Definition is the right fit because Data 360 components are not fully usable just because generic deployment succeeded. The consultant must complete the Data 360-specific lifecycle step so streams, mappings, insights, and rules are correctly registered in the target environment. The distractors fall short because they either move the problem into the wrong system, add needless duplication, ignore Data 360 object relationships, or rely on a feature built for a different lifecycle stage. In a real implementation, those choices usually create brittle pipelines, stale data, security exposure, or segments that look correct on paper but fail when activated. Thinking like an architect, the selected option places the logic where Data 360 can govern it and reuse it reliably. This is the nuance exam questions often test: the platform capability must match both the technical layer and the business timing requirement, not just sound related to data.
質問 # 42
Northern Trail Outfitters is using the Marketing Cloud Starter Data Bundles to bring Marketing Cloud data into Data Cloud.
What are two of the available datasets in Marketing Cloud Starter Data Bundles?
Choose 2 answers
正解：B、C
解説：
Explanation
The Marketing Cloud Starter Data Bundles are predefined data bundles that allow you to easily ingest data from Marketing Cloud into Data Cloud1. The available datasets in Marketing Cloud Starter Data Bundles are Email, MobileConnect, and MobilePush2. These datasets contain engagement events and metrics from different Marketing Cloud channels, such as email, SMS, and push notifications2. By using these datasets, you can enrich your Data Cloud data model with Marketing Cloud data and create segments and activations based on your marketing campaigns and journeys1. The other options are incorrect because they are not available datasets in Marketing Cloud Starter Data Bundles. Option A is incorrect because Personalization is not a dataset, but a feature of Marketing Cloud that allows you to tailor your content and messages to your audience3. Option C is incorrect because Loyalty Management is not a dataset, but a product of Marketing Cloud that allows you to create and manage loyaltyprograms for your customers4. References: Marketing Cloud Starter Data Bundles in Data Cloud, Connect Your Data Sources, Personalization in Marketing Cloud, Loyalty Management in Marketing Cloud
質問 # 43
Data Cloud receives a nightly file of all ecommerce transactions from the previous day.
Several segments and activations depend upon calculated insights from the updated data in order to maintain accuracy in the customer's scheduled campaign messages.
What should the consultant do to ensure the ecommerce data is ready for use for each of the scheduled activations?
正解：D
解説：
The best option that the consultant should do to ensure the ecommerce data is ready for use for each of the scheduled activations is A. Use Flow to trigger a change data event on the ecommerce data to refresh calculated insights and segments before the activations are scheduled to run. This option allows the consultant to use the Flow feature of Data Cloud, which enables automation and orchestration of data processing tasks based on events or schedules. Flow can be used to trigger a change data event on the ecommerce data, which is a type of event that indicates that the data has been updated or changed. This event can then trigger the refresh of the calculated insights and segments that depend on the ecommerce data, ensuring that they reflect the latest data. The refresh of the calculated insights and segments can be completed before the activations are scheduled to run, ensuring that the customer's scheduled campaign messages are accurate and relevant.
The other options are not as good as option A. Option B is incorrect because setting a refresh schedule for the calculated insights to occur every hour may not be sufficient or efficient. The refresh schedule may not align with the activation schedule, resulting in outdated or inconsistent data. The refresh schedule may also consume more resources and time than necessary, as the ecommerce data may not change every hour. Option C is incorrect because ensuring the activations are set to Incremental Activation and automatically publish every hour may not solve the problem. Incremental Activation is a feature that allows only the new or changed records in a segment to be activated, reducing the activation time and size. However, this feature does not ensure that the segment data is updated or refreshed based on the ecommerce data. The activation schedule may also not match the ecommerce data update schedule, resulting in inaccurate or irrelevant campaign messages. Option D is incorrect because ensuring the segments are set to Rapid Publish and set to refresh every hour may not be optimal or effective. Rapid Publish is a feature that allows segments to be published faster by skipping some validation steps, such as checking for duplicate records or invalid values.
However, this feature may compromise the quality or accuracy of the segment data, and may not be suitable for all use cases. The refresh schedule may also have the same issues as option B, as it may not sync with the ecommerce data update schedule or the activation schedule, resulting in outdated or inconsistent data. References: Salesforce Data Cloud Consultant Exam Guide, Flow, Change Data Events, Calculated Insights, Segments, [Activation]
質問 # 44
A company wants to test its marketing campaigns with different target populations.
What should the consultant adjust in the Segment Canvas interface to get different populations?
正解：D
解説：
Segmentation in Salesforce Data Cloud:
* The Segment Canvas interface is used to define and adjust target populations for marketing campaigns.
質問 # 45
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?
正解：C
解説：
* 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
質問 # 46
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