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Salesforce Data-Cloud-Consultant Exam Syllabus Topics:

TopicDetails
Topic 1
  • 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 2
  • 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 3
  • 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.

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Data-Cloud-Consultant Official Cert Guide - Salesforce Salesforce Certified Data 360 Consultant (Data-Con-101) - High Pass-Rate Data-Cloud-Consultant Exam Pass4sure

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Salesforce Certified Data 360 Consultant (Data-Con-101) Sample Questions (Q12-Q17):

NEW QUESTION # 12
How does Data 360 handle an individual ' s Right to Be Forgotten?

Answer: A

Explanation:
The governance lens is least privilege, purpose limitation, and honoring privacy operations against the individual profile. Deletes the specified Individual and records from any data model object/data lake object related to the Individual supports the governance requirement because Data 360 implementations should minimize unnecessary access, avoid over-collection, and process deletion or consent requests at the profile level where Salesforce expects them. The safest design is explicit, auditable, and limited to the business purpose. 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 # 13
Every day, Northern Trail Outfitters uploads a summary of the last 24 hours of store transactions to a new file in an Amazon S3 bucket, and files older than seven days are automatically deleted. Each file contains a timestamp in a standardized naming convention.
Which two options should a consultant configure when ingesting this data stream?
Choose 2 answers

Answer: C,D

Explanation:
When ingesting data from an Amazon S3 bucket, the consultant should configure the following options:
* The refresh mode should be set to "Upsert", which means that new and updated records will be added or updated in Data Cloud, while existing records will be preserved. This ensures that the data is always up to date and consistent with the source.
* The filename should contain a wildcard to accommodate the timestamp, which means that the file name pattern should include a variable part that matches the timestamp format. For example, if the file name is store_transactions_2023-12-18.csv, the wildcard could be store_transactions_*.csv. This ensures that the ingestion process can identify and process the correct file every day.
The other options are not necessary or relevant for this scenario:
* Deletion of old files is a feature of the Amazon S3 bucket, not the Data Cloud ingestion process. Data Cloud does not delete any files from the source, nor does it require the source files to be deleted after ingestion.
* Full Refresh is a refresh mode that deletes all existing records in Data Cloud and replaces them with the records from the source file. This is not suitable for this scenario, as it would result in data loss and inconsistency, especially if the source file only contains the summary of the last 24 hours of
* transactions. References: Ingest Data from Amazon S3, Refresh Modes


NEW QUESTION # 14
The Data Cloud admin at Northern Trail Outfitters (NTO) wants to be proactively and immediately informed via Slack and email if any of the data streams fail for any reason. If this happens, a case should also be triggered as part of NTO's existing support and triage process, and reflected in its global monitoring dashboard.
What should a consultant recommend for these requirements?

Answer: B

Explanation:
To meet the requirement of being proactively and immediately informed via Slack and email if any data streams fail, and to trigger a case as part of the support process, the best solution is to use Salesforce Flows .
Here's why and how this works:
Understanding the Requirements :
The admin wants to be notified immediately via Slack and email when a data stream fails.
A case should also be created automatically to reflect the issue in the global monitoring dashboard.
This requires an automated process that integrates with both internal systems (e.g., Slack, email) and external workflows (e.g., case creation).
Why Salesforce Flows?
Salesforce Flows are highly flexible and can automate complex business processes. They can monitor system events (e.g., data stream failures) and trigger actions like sending notifications or creating records.
Flows can integrate seamlessly with Slack and email using platform events and action elements.
They can also create cases programmatically and update dashboards for real-time monitoring.
Steps to Implement This Solution :
Step 1: Navigate to Setup > Process Automation > Flows and create a new flow.
Step 2: Configure a Platform Event Trigger or Record-Triggered Flow to listen for data stream failure events.
Step 3: Add an action element to send a notification to Slack using the Slack Integration feature.
Step 4: Add another action element to send an email alert using the Send Email action.
Step 5: Add a step to create a Case record with details about the failure. Use predefined fields to populate relevant information (e.g., error message, timestamp).
Step 6: Update the global monitoring dashboard to reflect the newly created case. This can be done by linking the case to a report or dashboard component.
Why Not Other Options?
A). Data actions: While data actions can perform specific tasks on data, they are not designed for cross-system automation like sending Slack notifications or creating cases.
B). Data Cloud Query Editor: The Query Editor is used for querying and analyzing data but does not provide automation capabilities for notifications or case creation.
D). Salesforce reports and dashboards: Reports and dashboards are for visualizing data, not for triggering actions or automating workflows.
By using Salesforce Flows, NTO can achieve a fully automated and integrated solution that meets all the stated requirements.


NEW QUESTION # 15
If a data source does not have a field that can be designated as a primary key, what should the consultant do?

Answer: C

Explanation:
Understanding Primary Keys in Salesforce Data Cloud:
* A primary key is a unique identifier for records in a data source. It ensures that each record can be uniquely identified and accessed.


NEW QUESTION # 16
Which configuration supports separate Amazon S3 buckets for data ingestion and activation?

Answer: B

Explanation:
To support separate Amazon S3 buckets for data ingestion and activation, you need to configure dedicated S3 data sources in Data Cloud setup. Data sources are used to identify the origin and type of the data that you ingest into Data Cloud1. You can create different data sources for each S3 bucket that you want to use for ingestion or activation, and specify the bucket name, region, and access credentials2. This way, you can separate and organize your data by different criteria, such as brand, region, product, or business unit3. The other options are incorrect because they do not support separate S3 buckets for data ingestion and activation. Multiple S3 connectors are not a valid configuration in Data Cloud setup, as there is only one S3 connector available4. Dedicated S3 data sources in activation setup are not a valid configuration either, as activation setup does not require data sources, but activation targets5. Separate user credentials for data stream and activation target are not sufficient to support separate S3 buckets, as you also need to specify the bucket name and region for each data source2. References: Data Sources Overview, Amazon S3 Storage Connector, Data Spaces Overview, Data Streams Overview, Data Activation Overview


NEW QUESTION # 17
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