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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 |
| Exam Format: | Scenario-based questions, Multiple-choice, Multiple-select |
| Available Languages: | English |
| Exam Duration: | 105 minutes |
| Real Exam Qty: | 60 (plus up to 5 unscored questions) |
| Certificate Validity Period: | 3 years |
| Exam Price: | USD $200 + applicable taxes |
| Passing Score: | 62% - 70% |
| Related Certifications: | Salesforce Certified Marketing Cloud Consultant Salesforce Certified Data Architect Salesforce Certified Administrator |
| 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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NEW QUESTION # 96
Northern Trail Outfitters (NTO), an outdoor lifestyle clothing brand, recently started a new line of business. The new business specializes in gourmet camping food. For business reasons as well as security reasons, it's important to NTO to keep all Data Cloud data separated by brand.
Which capability best supports NTO's desire to separate its data by brand?
Answer: D
Explanation:
Data spaces are logical containers that allow you to separate and organize your data by different criteria, such as brand, region, product, or business unit1. Data spaces can help you manage data access, security, and governance, as well as enable cross-cloud data integration and activation2. For NTO, data spaces can support their desire to separate their data by brand, so that they can have different data models, rules, and insights for their outdoor lifestyle clothing and gourmet camping food businesses. Data spaces can also help NTO comply with any data privacy and security regulations that may apply to their different brands3. The other options are incorrect because they do not provide the same level of data separation and organization as data spaces. Data streams are used to ingest data from different sources into Data Cloud, but they do not separate the data by brand4. Data model objects are used to define the structure and attributes of the data, but they do not isolate the data by brand5. Data sources are used to identify the origin and type of the data, but they do not partition the data by brand. Reference: Data Spaces Overview, Create Data Spaces, Data Privacy and Security in Data Cloud, Data Streams Overview, Data Model Objects Overview, [Data Sources Overview]
NEW QUESTION # 97
Cloud Kicks received a Request to be Forgotten by a customer.
In which two ways should a consultant use Data Cloud to honor this request?
Choose 2 answers
Answer: A,B
Explanation:
To honor a Request to be Forgotten by a customer, a consultant should use Data Cloud in two ways:
* Add the Individual ID to a headerless file and use the delete from file functionality. This option allows the consultant to delete multiple Individuals from Data Cloud by uploading a CSV file with their IDs1. The deletion process is asynchronous and can take up to 24 hours to complete1.
* Use the Consent API to suppress processing and delete the Individual and related records from source data streams. This option allows the consultant to submit a Data Deletion request for an Individual profile in Data Cloud using the Consent API2. A Data Deletion request deletes the specified Individual entity and any entities where a relationship has been defined between that entity's identifying attribute and the Individual ID attribute2. The deletion process is reprocessed at 30, 60, and 90 days to ensure a full deletion2. The other options are not correct because:
* Deleting the data from the incoming data stream and performing a full refresh will not delete the existing data in Data Cloud, only the new data from the source system3.
* Using Data Explorer to locate and manually remove the Individual will not delete the related records from the source data streams, only the Individual entity in Data Cloud. References:
* Delete Individuals from Data Cloud
* Requesting Data Deletion or Right to Be Forgotten
* Data Refresh for Data Cloud
* [Data Explorer]
NEW QUESTION # 98
What is the minimum requirement needed when using the Visual Insights Builder to create a calculated insight?
Answer: D
Explanation:
The analytics requirement determines whether the logic belongs in an insight, a semantic metric, or a query- time layer. At least one measure and one dimension matches the need because the business is asking for reusable metrics, dimensions, or aggregation behavior that consumers can filter and analyze. Data 360 separates raw harmonized data from analytical definitions so that dashboards, Tableau experiences, and segment logic remain consistent. 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.
NEW QUESTION # 99
What are the two minimum requirements needed when using the Visual Insights Builder to create a calculated insight?
Choose 2 answers
Answer: A,B
Explanation:
* Introduction to Visual Insights Builder:
The Visual Insights Builder in Salesforce Data Cloud is a tool used to create calculated insights, which are custom metrics derived from the existing data.
Reference:
* Requirements for Creating Calculated Insights:
Measure: A measure is a quantitative value that you want to analyze, such as revenue, number of purchases, or total time spent on a platform.
Dimension: A dimension is a qualitative attribute that you use to categorize or filter the measures, such as date, region, or customer segment.
* Steps to Create a Calculated Insight:
Navigate to the Visual Insights Builder within Salesforce Data Cloud.
Select "Create New Insight" and choose the dataset.
Add at least one measure: This could be any metric you want to analyze, such as "Total Sales." Add at least one dimension: This helps to break down the measure, such as "Sales by Region."
* Practical Application:
Example: To create an insight on "Average Purchase Value by Region," you would need:
A measure: Total Purchase Value.
A dimension: Customer Region.
This allows for actionable insights, such as identifying high-performing regions.
NEW QUESTION # 100
A customer is concerned that the consolidation rate displayed in the identity resolution is quite low compared to their initial estimations.
Which configuration change should a consultant consider in order to increase the consolidation rate?
Answer: B
Explanation:
Explanation
The consolidation rate is the amount by which source profiles are combined to produce unified profiles, calculated as 1 - (number of unified individuals / number of source individuals). For example, if you ingest
100 source records and create 80 unified profiles, your consolidation rate is 20%. To increase the consolidation rate, you need to increase the number of matches between source profiles, which can be done by adding more match rules. Match rules define the criteria for matching source profiles based on their attributes.
By increasing the number of match rules, you can increase the chances of finding matches between source profiles and thus increase the consolidation rate. On the other hand, changing reconciliation rules, including additional attributes, or reducing the number of match rules can decrease the consolidation rate, as they can either reduce the number of matches or increase the number of unified profiles. References: Identity Resolution Calculated Insight: Consolidation Rates for Unified Profiles, Identity Resolution Ruleset Processing Results, Configure Identity Resolution Rulesets
NEW QUESTION # 101
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