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Salesforce Data-Cloud-Consultant Exam Overview:

Certification Vendor:	Salesforce
Exam Name:	Salesforce Certified Data 360 Consultant (formerly Salesforce Certified Data Cloud Consultant)
Exam Number:	Data-Con-101 / Data-Cloud-Consultant
Related Certifications:	Salesforce Certified Data Architect Salesforce Certified Marketing Cloud Consultant Salesforce Certified Administrator
Exam Duration:	105 minutes
Certificate Validity Period:	3 years
Passing Score:	62% - 70%
Exam Price:	USD $200 + applicable taxes
Real Exam Qty:	60 (plus up to 5 unscored questions)
Exam Format:	Multiple-select, Scenario-based questions, Multiple-choice
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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Salesforce Data-Cloud-Consultant Exam Syllabus Topics:

Topic	Details
Topic 1	Data Cloud Setup and Administration: This topic includes applying Data Cloud permissions, permission sets, org-wide settings. It describes and configures data stream types, and data bundles. Moreover, it discusses use cases for data spaces, creating data spaces, managing and administering Data Cloud using reports, dashboards, flows, packaging, data kits, diagnosing and exploring data using Data Explorer, Profile Explorer, and APIs.
Topic 2	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 3	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.
Topic 4	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.

Salesforce Certified Data 360 Consultant (Data-Con-101) Sample Questions (Q89-Q94):

NEW QUESTION # 89
Northern Trail Outfitters (NTO) asks its Data Cloud consultant for a list of contacts who fit within a certain segment for a mailing campaign.
How should the consultant provide this list to NTO?

A. Create a new file storage activation target, create the segment, and then activate the segment to the new activation target.
B. Create the segment, select Email as the activation target, and activate the segment di nearly to NTO.
C. Create the segment and then click Download to obtain the segment membership details to provide to NTO.
D. Create the segment and then activate the segment to NTO's Salesforce CRM.

Answer: A

Explanation:
Segment Creation in Data Cloud: Salesforce Data Cloud allows the creation of segments based on specific criteria for targeted marketing campaigns.
Activation Targets: After creating a segment, it must be activated to make the data available for use. Various activation targets can be configured based on how the segment data will be used.
File Storage Activation Target: To provide a list of contacts fitting a segment, creating a file storage activation target allows the segment data to be exported as a file. This file can then be shared with NTO for their mailing campaign.
Process:
* Define the segment criteria in Salesforce Data Cloud.
* Create a new file storage activation target.
* Activate the segment to this target, which generates a downloadable file containing the segment membership details.
References:
* Salesforce Data Cloud Documentation: Segmentation
* Salesforce Data Cloud Activation

NEW QUESTION # 90
When reporting on calculated insights in Salesforce, what is a critical limitation a Data 360 Consultant must keep in mind regarding data freshness?

A. Calculated insights can only be reported on if they contain fewer than 2,000 total rows.
B. The data reflects the state of the last time the insight was batch processed.
C. Calculated insights are only updated once every 24 hours.
D. Insights are only available in reports if they have been " Activated " to a Marketing Cloud engagement.

Answer: B

Explanation:
The analytics requirement determines whether the logic belongs in an insight, a semantic metric, or a query- time layer. The data reflects the state of the last time the insight was batch processed. 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.

NEW QUESTION # 91
During an implementation project, a consultant completed ingestion of all data streams for their customer.
Prior to segmenting and acting on that data, which additional configuration is required?

A. Data Activation
B. Identity Resolution
C. Calculated Insights
D. Data Mapping

Answer: B

Explanation:
Explanation
After ingesting data from different sources into Data Cloud, the additional configuration that is required before segmenting and acting on that data is Identity Resolution. Identity Resolution is the process of matching and reconciling source profiles from different data sources and creating unified profiles that represent a single individual or entity1. Identity Resolution enables you to create a 360-degree view of your customers and prospects, and to segment and activate them based on their attributes and behaviors2. To configure Identity Resolution, you need to create and deploy a ruleset that defines the match rules and reconciliation rules for your data3. The other options are incorrect because they are not required before segmenting and acting on the data. Data Activation is the process of sending data from Data Cloud to other Salesforce clouds or external destinations for marketing, sales, or service purposes4. Calculated Insights are derived attributes that are computed based on the source or unified data, such as lifetime value, churn risk, or product affinity5. Data Mapping is the process of mapping source attributes to unified attributes in the data model. These configurations can be done after segmenting and acting on the data, or in parallel with Identity Resolution, but they are not prerequisites for it. References: Identity Resolution Overview, Segment and Activate Data in Data Cloud, Configure Identity Resolution Rulesets, Data Activation Overview, Calculated Insights Overview,
[Data Mapping Overview]

NEW QUESTION # 92
Which statement about query federation in Data 360 is true?

A. Query federation requires file-based data lakes such as Iceberg.
B. Query federation requires data to be first converted to parquet format.
C. Data 360 executes queries using its own compute engine, regardless of the external system.
D. Query federation pushes SQL queries to the external system ' s compute layer.

Answer: D

Explanation:
The architecture principle is to avoid unnecessary data movement when the external platform can be queried or shared securely. Query federation pushes SQL queries to the external system ' s compute layer. aligns with the zero-copy model because Data 360 can expose or query governed data without building another extract pipeline. That is important when teams want freshness, reduced duplication, and lower operational burden while still respecting permissions and platform boundaries. 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 # 93
Which statement about Data 360 ' s Web and Mobile Application Connector is true?

A. The Tenant Specific Endpoint is auto-generated in Data 360 when setting the connector.
B. Any data streams associated with the connector will be automatically deleted upon deleting the app from Data 360 Setup.
C. The connector schema can be updated to delete an existing field.
D. A standard schema containing event, profile, and transaction data is created at the time the connector is configured.

Answer: A

Explanation:
The design point is to preserve source fidelity while shaping data only where Data 360 processing needs it.
Here, The Tenant Specific Endpoint is auto-generated in Data 360 when setting the connector. fits because it changes the shape, keying, or refresh behavior at the Data 360 layer instead of forcing the source system to carry an analytics-specific design. In production, this keeps the upstream application simpler and gives the data team a repeatable way to prepare records for mapping, identity resolution, insights, or segmentation. 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.

NEW QUESTION # 94
......

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