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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
  • 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.
トピック 2
  • 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 3
  • 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.
トピック 4
  • 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 5
  • 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.

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Salesforce Certified Data 360 Consultant (Data-Con-101) 認定 Data-Cloud-Consultant 試験問題 (Q24-Q29):

質問 # 24
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

正解：B、C

解説：
source data streams.
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. Reference:
Delete Individuals from Data Cloud
Requesting Data Deletion or Right to Be Forgotten
Data Refresh for Data Cloud
[Data Explorer]


質問 # 25
A consultant is integrating an Amazon 53 activated campaign with the customer's destination system.
In order for the destination system to find the metadata about the segment, which file on the 53 will contain this information for processing?

正解：D

解説：
The file on the Amazon S3 that will contain the metadata about the segment for processing is B. The json file. The json file is a metadata file that is generated along with the csv file when a segment is activated to Amazon S3. The json file contains information such as the segment name, the segment ID, the segment size, the segment attributes, the segment filters, and the segment schedule. The destination system can use this file to identify the segment and its properties, and to match the segment data with the corresponding fields in the destination system. References: Salesforce Data Cloud Consultant Exam Guide, Amazon S3 Activation


質問 # 26
Northern Trail Outfitters uploads new customer data to an Amazon S3 bucket on a daily basis to be ingested in Data 360. Based on this, a calculated insight is created that shows the total spend per customer in the last
30 days. In which sequence should each process be run to ensure that freshly imported data is ready and available to use for any segment?

正解：C

解説：
The design point is to preserve source fidelity while shaping data only where Data 360 processing needs it.
Here, Refresh Data Stream > Identity Resolution > Calculated Insight 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.


質問 # 27
Cumulus Financial uses calculated insights to compute the total banking value per branch for its high net worth customers. In the calculated insight, "banking value" is a metric, "branch" is a dimension, and "high net worth" is a filter.
What can be included as an attribute in activation?

正解：B

解説：
According to the Salesforce Data Cloud documentation, an attribute is a dimension or a measure that can be used in activation. A dimension is a categorical variable that can be used to group or filter data, such as branch, region, or product. A measure is a numerical variable that can be used to calculate metrics, such as revenue, profit, or count. A filter is a condition that can be applied to limit the data that is used in a calculated insight, such as high net worth, age range, or gender. In this question, the calculated insight uses "banking value" as a metric, which is a measure, and "branch" as a dimension. Therefore, only "branch" can be included as an attribute in activation, since it is a dimension. The other options are either measures or filters, which are not attributes. References: Data Cloud Permission Sets, Salesforce Data Cloud Exam Questions


質問 # 28
A Data 360 Consultant is configuring a zero- copy architecture where an external Snowflake instance needs to access Data 360 data without the latency of traditional extract, transform, load (ETL) processes. Which capability should the consultant use to expose Data 360 objects to the external Snowflake environment?

正解：B

解説：
The architecture principle is to avoid unnecessary data movement when the external platform can be queried or shared securely. Data 360 Data Shares 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.


質問 # 29
......

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