QUESTION: 49

A segment fails to refresh with the error "Segment references too many data lake objects (DLOS)".
Which two troubleshooting tips should help remedy this issue? Choose 2 answers

Split the segment into smaller segments.
Use calculated insights in order to reduce the complexity of the segmentation query.
Refine segmentation criteria to limit up to five custom data model objects (DMOs).
Space out the segment schedules to reduce DLO load.

Answer(s): A,B

Explanation:

The error "Segment references too many data lake objects (DLOs)" occurs when a segment query exceeds the limit of 50 DLOs that can be referenced in a single query. This can happen when the segment has too many filters, nested segments, or exclusion criteria that involve different DLOs. To remedy this issue, the consultant can try the following troubleshooting tips:
Split the segment into smaller segments. The consultant can divide the segment into multiple segments that have fewer filters, nested segments, or exclusion criteria. This can reduce the number of DLOs that are referenced in each segment query and avoid the error. The consultant can then use the smaller segments as nested segments in a larger segment, or activate them separately. Use calculated insights in order to reduce the complexity of the segmentation query. The consultant can create calculated insights that are derived from existing data using formulas. Calculated insights can simplify the segmentation query by replacing multiple filters or nested segments with a single attribute. For example, instead of using multiple filters to segment individuals based on their purchase history, the consultant can create a calculated insight that calculates the lifetime value of each individual and use that as a filter.
The other options are not troubleshooting tips that can help remedy this issue. Refining segmentation criteria to limit up to five custom data model objects (DMOs) is not a valid option, as the limit of 50 DLOs applies to both standard and custom DMOs. Spacing out the segment schedules to reduce DLO load is not a valid option, as the error is not related to the DLO load, but to the segment query complexity.

Reference:

Troubleshoot Segment Errors
Create a Calculated Insight

Create a Segment in Data Cloud

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QUESTION: 50

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

Answer(s): A

Explanation:

: Value suggestion is a Data Cloud feature that allows users to see and select the possible values for a text field when creating segment filters. Value suggestion can be enabled or disabled for each data model object (DMO) field in the DMO record home. Value suggestion can help users to identify and select text attributes from a picklist of options, without having to type or remember the exact values. Value suggestion can also reduce errors and improve data quality by ensuring consistent and valid values for the segment filters.

Reference:

Use Value Suggestions in Segmentation, Considerations for Selecting Related Attributes

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QUESTION: 51

A consultant is working in a customer's Data Cloud org and is asked to delete the existing identity resolution ruleset.
Which two impacts should the consultant communicate as a result of this action? Choose 2 answers

All individual data will be removed.
Unified customer data associated with this ruleset will be removed.
Dependencies on data model objects will be removed.
All source profile data will be removed

Answer(s): B,C

Explanation:

Deleting an identity resolution ruleset has two major impacts that the consultant should communicate to the customer. First, it will permanently remove all unified customer data that was created by the ruleset, meaning that the unified profiles and their attributes will no longer be available in Data Cloud. Second, it will eliminate dependencies on data model objects that were used by the ruleset, meaning that the data model objects can be modified or deleted without affecting the ruleset. These impacts can have significant consequences for the customer's data quality, segmentation, activation, and analytics, so the consultant should advise the customer to carefully consider the implications of deleting a ruleset before proceeding. The other options are incorrect because they are not impacts of deleting a ruleset. Option A is incorrect because deleting a ruleset will not remove all individual data, but only the unified customer data. The individual data from the source systems will still be available in Data Cloud. Option D is incorrect because deleting a ruleset will not remove all source profile data, but only the unified customer data. The source profile data from the data streams will still be available in Data Cloud.

Reference:

Delete an Identity Resolution Ruleset

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QUESTION: 52

Northern Trail Outfitters uploads new customer data to an Amazon S3 Bucket on a daily basis to be ingested in Data Cloud.
In what order should each process be run to ensure that freshly imported data is ready and available to use for any segment?

Calculated Insight > Refresh Data Stream > Identity Resolution
Refresh Data Stream > Calculated Insight > Identity Resolution
Identity Resolution > Refresh Data Stream > Calculated Insight
Refresh Data Stream > Identity Resolution > Calculated Insight

Answer(s): D

Explanation:

To ensure that freshly imported data from an Amazon S3 Bucket is ready and available to use for any segment, the following processes should be run in this order:
Refresh Data Stream: This process updates the data lake objects in Data Cloud with the latest data from the source system. It can be configured to run automatically or manually, depending on the data stream settings. Refreshing the data stream ensures that Data Cloud has the most recent and accurate data from the Amazon S3 Bucket.
Identity Resolution: This process creates unified individual profiles by matching and consolidating source profiles from different data streams based on the identity resolution ruleset. It runs daily by default, but can be triggered manually as well. Identity resolution ensures that Data Cloud has a single view of each customer across different data sources. Calculated Insight: This process performs calculations on data lake objects or CRM data and returns a result as a new data object. It can be used to create metrics or measures for segmentation or analysis purposes. Calculated insights ensure that Data Cloud has the derived data that can be used for personalization or activation.

Reference:

1: Configure Data Stream Refresh and Frequency - Salesforce
2: Identity Resolution Ruleset Processing Results - Salesforce
3: Calculated Insights - Salesforce

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Free Data-Cloud-Consultant Exam Braindumps (page: 13)

QUESTION: 49

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QUESTION: 50

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QUESTION: 51

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QUESTION: 52

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