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Salesforce Data-Cloud-Consultant 認定試験の出題範囲：

トピック	出題範囲
トピック 1	Act on Data: This topic defines activations and their basic use cases, using attributes and related attributes, identifying and analyzing timing dependencies affecting the Data Cloud lifecycle. Additionally it focuses on troubleshooting common problems with activations, and using data actions, including their requirements and intended use cases.
トピック 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.
トピック 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.
トピック 4	Segmentation and Insights: This topic defines basic concepts of segmentation and use cases, identifies scenarios for analyzing segment membership, configuring, refining, and maintaining segments within Data Cloud, and differentiating between calculated and streaming insights.
トピック 5	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.

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Salesforce Certified Data 360 Consultant (Data-Con-101) 認定 Data-Cloud-Consultant 試験問題 (Q94-Q99):

質問 # 94
A customer is interested in tracking their Average Time To Close for Service Cloud cases. They are looking for a flexible solution that provides near real- time reporting and allows different teams to review the data across the relevant dimensions for that team coming from Sales, Service, Marketing, and Commerce Clouds.
Which solution meets the customer ' s needs?

A. Service Cloud Reports
B. Data Model Object (DMO) Formula Fields
C. Calculated Insights
D. Semantic Model Metrics

正解：D

解説：
The AI pattern works when the model is grounded in appropriate Data 360 data and its outputs can be operationalized safely. Semantic Model Metrics fits because predictions or generative experiences are only useful when the data is representative, governed, and connected to Salesforce execution patterns such as scoring jobs, Flow, or grounded retrieval. 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 # 95
A customer is trying to activate data from Data Cloud to an Amazon S3 Cloud File Storage Bucket.
Which authentication type should the consultant recommend to connect to the S3 bucket from Data Cloud?

A. Use an S3 Access Key and Secret Key.
B. Use an S3 Encrypted Username and Password.
C. Use an S3 Private Key Certificate.
D. Use a JWT Token generated on S3.

正解：A

解説：
To use the Amazon S3 Storage Connector in Data Cloud, the consultant needs to provide the S3 bucket name, region, and access key and secret key for authentication. The access key and secret key are generated by AWS and can be managed in the IAM console. The other options are not supported by the S3 Storage Connector or by Data Cloud. Reference: Amazon S3 Storage Connector - Salesforce, How to Use the Amazon S3 Storage Connector in Data Cloud | Salesforce Developers Blog Learn more
1help.salesforce.com2developer.salesforce.com

質問 # 96
A retailer wants to unify profiles using Loyalty ID which is different than the unique ID of their customers.
Which object should the consultant use in identity resolution to perform exact match rules on the Loyalty ID?

A. Loyalty Identification object
B. Contact Identification object
C. Party Identification object
D. Individual object

正解：C

解説：
The Party Identification object is the correct object to use in identity resolution to perform exact match rules on the Loyalty ID. The Party Identification object is a child object of the Individual object that stores different types of identifiers for an individual, such as email, phone, loyalty ID, social media handle, etc. Each identifier has a type, a value, and a source. The consultant can use the Party Identification object to create a match rule that compares the Loyalty ID type and value across different sources and links the corresponding individuals.
The other options are not correct objects to use in identity resolution to perform exact match rules on the Loyalty ID. The Loyalty Identification object does not exist in Data Cloud. The Individual object is the parent object that represents a unified profile of an individual, but it does not store the Loyalty ID directly. The Contact Identification object is a child object of the Contact object that stores identifiers for a contact, such as email, phone, etc., but it does not store the Loyalty ID.
Reference:
Data Modeling Requirements for Identity Resolution
Identity Resolution in a Data Space
Configure Identity Resolution Rulesets
Map Required Objects
Data and Identity in Data Cloud

質問 # 97
Northern Trail Outfitters (NTD) creates a calculated insight to compute recency, frequency, monetary {RFM) scores on its unified individuals. NTO then creates a segment based on these scores that it activates to a Marketing Cloud activation target.
Which two actions are required when configuring the activation?
Choose 2 answers

A. Choose a segment.
B. Add the calculated insight in the activation.
C. Add additional attributes.
D. Select contact points.

正解：A、D

解説：
To configure an activation to a Marketing Cloud activation target, you need to choose a segment and select contact points. Choosing a segment allows you to specify which unified individuals you want to activate.
Selecting contact points allows you to map the attributes from the segment to the fields in the Marketing Cloud data extension. You do not need to add additional attributes or add the calculated insight in the activation, as these are already part of the segment definition. References: Create a Marketing Cloud Activation Target; Types of Data Targets in Data Cloud

質問 # 98
A solution architect needs to create a segment of " High Value Customers " . They define this as anyone who qualifies for the existing Platinum Loyalty segment OR anyone who has spent more than US$5,000. What is the most efficient way to build this?

A. Create a waterfall segment, prioritizing the " Platinum Loyalty " group first and the " High Spender " group second.
B. Create two separate segments and join them together in a Tableau dashboard for activation.
C. Build a calculated insight that joins both conditions and use that as the only filter in a new segment.
D. Use a nested segment for " Platinum Loyalty " and add a separate container for the minimum spend with an OR operator.

正解：D

解説：
The segmentation and activation design starts with grain: who or what the audience represents, and which attributes must travel with it. Use a nested segment for " Platinum Loyalty " and add a separate container for the minimum spend with an OR operator. works because Data 360 segmentation and activation must respect audience grain, relationship paths, and activation payload rules. A segment can qualify the audience, but activation determines which related attributes or contact points are actually sent downstream. 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.

質問 # 99
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