Pass Data-Cloud-Consultant Exam with Updated Data-Cloud-Consultant Exam Dumps PDF 2026 [Q45-Q66]

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Pass Data-Cloud-Consultant Exam with Updated Data-Cloud-Consultant Exam Dumps PDF 2026

Data-Cloud-Consultant Exam Dumps – Free Demo & 365 Day Updates

Salesforce Data-Cloud-Consultant Exam Syllabus Topics:

Topic	Details
Topic 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.
Topic 2	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.
Topic 3	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.

NO.45 A customer has two Data Cloud orgs. A new configuration has been completed and tested for an Amazon S3 data stream and its mappings in one of the Data Cloud orgs.
What is recommended to package and promote this configuration to the customer’s second org?

Use the Metadata API.

Use the Salesforce CRM connector.

Create a data kit.

Package as an AppExchange application.

NO.46 During discovery, which feature should a consultant highlight for a customer who has multiple data sources and needs to match and reconcile data about individuals into a single unified profile?

Data Cleansing

Harmonization

Data Consolidation

Identity Resolution

NO.47 What is the primary purpose of Data Cloud?

Providing a golden record of a customer

Managing sales cycles and opportunities

Analyzing marketing data results

Integrating and unifying customer data

NO.48 What is a reason to create a formula when ingesting a data stream?

To concatenate files so they are ingested in the correct sequence

To remove duplicate rows of data from the data stream

To add a unique external identifier to an existing ruleset

To transform a datetime field into a date field for use in data mapping

NO.49 A customer creates a large segment of customers that placed orders in the last 30 days, and adds related attributes from the… to the activation. Upon checking the activation in Marketing Cloud, they notice It contains orders that are older than 30 days.
What should a consultant do to resolve this issue?

use data graphs that contain only 30 days of data.

Apply a data space fitter to exclude orders older than 30 days.

Apply a filter to Purchase Order Date to exclude orders older than 30 days.

Use SQL in Marketing Cloud Engagement to remove orders older than 30 days.

NO.50 Northern Trail Outfitters asks its consultant to extract the runner profiles and activity logs from its Track My Run mobile app and load them into Data Cloud. The marketing department also indicates that they need the last 90 days of historical data and want all new and updated data as it becomes available on a go-forward basis.
As best practice, which sequence of actions should the consultant use to implement this request?

Use bulk ingestion to first load the last 90 days of data, and also subsequently use bulk ingestion to synchronize the future data as It becomes available.

Use streaming ingestion to first load the last 90 days of data, and also subsequently use streaming ingestion synchronize future data as It becomes available.

Use streaming ingestion to first load the last 90 days of data, and then use bulk Ingestion to synchronize future data as It becomes available.

Use bulk ingestion to first load the last 90 days of data, and then use streaming ingestion to synchronize future data as It becomes available.

NO.51 A lead architect needs to build a real-time Customer Health Dashboard in a custom web portal that displays a unified customer ‘ s recent purchase history (Engagement data) and their calculated loyalty score. Which API strategy is most appropriate to meet this requirement?

Use the Metadata API to retrieve the schema of the unified profile, then use a standard REST GET call on the Individual object.

Use the Query API to send an SQL/SOQL-based request to join data to retrieve a comprehensive view.

Use the Profile API because it is optimized for high-speed retrieval of unified profile attributes and calculated insights.

Use the Ingestion API to push the dashboard requirements into a data stream to trigger a webhook.

NO.52 What does the Ignore Empty Value option do in identity resolution?

Ignores empty fields when running any custom match rules

Ignores empty fields when running reconciliation rules

Ignores Individual object records with empty fields when running identity resolution rules

Ignores empty fields when running the standard match rules

NO.53 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?

Data actions

Data Cloud Query Editor

Salesforce flows

Salesforce reports and dashboards

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.

NO.54 An organization wants to enable users with the ability to identify and select text attributes from a picklist of options.
Which Data Cloud feature should help with this use case?

Value suggestion

Data harmonization

Transformation formulas

Global picklists

NO.55 A customer notices that their consolidation rate is low across their account unification. They have mapped Account to the Individual and Contact Point Email DMOs.
What should they do to increase their consolidation rate?

Change reconciliation rules to Most Occurring.

Disable the individual identity ruleset.

Increase the number of matching rules.

Update their account address details in the data source

NO.56 Cumulus Financial uses Service Cloud as its CRM and stores mobile phone, home phone, and work phone as three separate fields for its customers on the Contact record. The company plans to use Data Cloud and ingest the Contact object via the CRM Connector.
What is the most efficient approach that a consultant should take when ingesting this data to ensure all the different phone numbers are properly mapped and available for use in activation?

Ingest the Contact object and map the Work Phone, Mobile Phone, and Home Phone to the Contact Point Phone data map object from the Contact data stream.

Ingest the Contact object and use streaming transforms to normalize the phone numbers from the Contact data stream into a separate Phone data lake object (DLO) that contains three rows, and then map this new DLO to the Contact Point Phone data map object.

Ingest the Contact object and then create a calculated insight to normalize the phone numbers, and then map to the Contact Point Phone data map object.

Ingest the Contact object and create formula fields in the Contact data stream on the phone numbers, and then map to the Contact Point Phone data map object.

The most efficient approach that a consultant should take when ingesting this data to ensure all the different phone numbers are properly mapped and available for use in activation is B. Ingest the Contact object and use streaming transforms to normalize the phone numbers from the Contact data stream into a separate Phone data lake object (DLO) that contains three rows, and then map this new DLO to the Contact Point Phone data map object. This approach allows the consultant to use the streaming transforms feature of Data Cloud, which enables data manipulation and transformation at the time of ingestion, without requiring any additional processing or storage. Streaming transforms can be used to normalize the phone numbers from the Contact data stream, such as removing spaces, dashes, or parentheses, and adding country codes if needed. The normalized phone numbers can then be stored in a separate Phone DLO, which can have one row for each phone number type (work, home, mobile). The Phone DLO can then be mapped to the Contact Point Phone data map object, which is a standard object that represents a phone number associated with a contact point. This way, the consultant can ensure that all the phone numbers are available for activation, such as sending SMS messages or making calls to the customers.
The other options are not as efficient as option B. Option A is incorrect because it does not normalize the phone numbers, which may cause issues with activation or identity resolution. Option C is incorrect because it requires creating a calculated insight, which is an additional step that consumes more resources and time than streaming transforms. Option D is incorrect because it requires creating formula fields in the Contact data stream, which may not be supported by the CRM Connector or may cause conflicts with the existing fields in the Contact object. Reference: Salesforce Data Cloud Consultant Exam Guide, Data Ingestion and Modeling, Streaming Transforms, Contact Point Phone

NO.57 A consultant wants to ensure that every segment managed by multiple brand teams adheres to the same set of exclusion criteria, that are updated on a monthly basis.
What is the most efficient option to allow for this capability?

Create, publish, and deploy a data kit.

Create a reusable container block with common criteria.

Create a nested segment.

Create a segment and copy it for each brand.

NO.58 What is a reason to create a formula when ingesting a data stream?

To concatenate files so they are ingested in the correct sequence

To add a unique external identifier to an existing ruleset

To transform is date time field into a dale field for use in data mapping

To remove duplicate rows of data from the data stream

NO.59 How does Data Cloud ensure data privacy and security?

By encrypting data at rest and in transit

By enforcing and controlling consent references

By securely storing data in an offsite server

BY limiting data access to authorized admins

NO.60 A consultant is helping a beauty company ingest its profile data into Data Cloud. The company’s source data includes several fields, such as eye color, skin type, and hair color, that are not fields in the standard Individual data model object (DMO).
What should the consultant recommend to map this data to be used for both segmentation and identity resolution?

Create a custom DMO from scratch that has all fields that are needed.

Create a custom DMO with only the additional fields and map it to the standard Individual DMO.

Create custom fields on the standard Individual DMO.

Duplicate the standard Individual DMO and add the additional fields.

NO.61 A Data 360 Consultant is setting up a data stream with transactional data. Which field type should the consultant choose to ensure that leading zeros in the purchase order number are preserved?

Number

Decimal

Text

Serial

NO.62 A customer has multiple team members who create segment audiences that work in different time zones. One team member works at the home office in the Pacific time zone, that matches the org Time Zone setting. Another team member works remotely in the Eastern time zone.
Which user will see their home time zone in the segment and activation schedule areas?

The team member in the Pacific time zone.

The team member in the Eastern time zone.

Neither team member; Data Cloud shows all schedules in GMT.

Both team members; Data Cloud adjusts the segment and activation schedules to the time zone of the logged-in user

NO.63 Northern Trail Outfitters (NTO) wants to send a promotional campaign to customers that have purchased within the past 6 months. The Data 360 Consultant creates a segment to meet this requirement. Now, NTO has brought an additional requirement to suppress customers who have made purchases within the last week.
What should the consultant use to remove the recent customers?

Segmentation exclude rules

Streaming insights

Batch transforms

Related attributes

NO.64 What is the result of a segmentation criteria filtering on City | Is Equal To | ‘San Jose’?

Cities containing ‘San Jose’, ‘San Jose’, ‘san jose’, or ‘san jose’

Cities only containing ‘San Jose’ or ‘san jose’

Cities only containing ‘San Jose’ or ‘San Jose’

Cities only containing ‘San Jose’ or ‘san jose’

NO.65 To import campaign members into a campaign in Salesforce CRM, a user wants to export the segment to Amazon S3. The resulting file needs to include the Salesforce CRM Campaign ID in the name.
What are two ways to achieve this outcome?
Choose 2 answers

Include campaign identifier in the activation name.

Hard code the campaign identifier as a new attribute in the campaign activation.

Include campaign identifier in the filename specification.

Include campaign identifier in the segment name.

NO.66 What is a key functionality of Data Cloud?

To create a master data management (MUM) strategy

To give a persistent ID for unified profiles

To build insights on unified profiles

To help users build a heat map using their data