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Free Data-Cloud-Consultant Exam Braindumps (page: 23)

Page 22 of 44
PDF with 170 Questions

Northern Trail Outfitters unifies individuals in its Data Cloud instance.
Which three features ca e consultant use to validate the data on a unified profile? Choose 3 answers

  1. Identity Resolution
  2. Query APL
  3. Data Explorer
  4. Profile Explorer
  5. Data Actions

Answer(s): A,C,D

Explanation:

To validate the data on a unified profile, the consultant can use the following features:

Identity Resolution: This feature allows the consultant to view and edit the identity resolution rulesets that determine how individuals are unified from different data sources. Data Explorer: This feature allows the consultant to browse and filter the unified profiles and view their attributes, segments, and activities.
Profile Explorer: This feature allows the consultant to drill down into a specific unified profile and view its details, such as source records, identity graph, calculated insights, and data actions.


Reference:

1: Identity Resolution in Data Cloud
2: Data Explorer in Data Cloud
3: Profile Explorer in Data Cloud



A Data Cloud consultant recently discovered that their identity resolution process is matching individuals that share email addresses or phone numbers, but are not actually the same individual.
What should the consultant do to address this issue?

  1. Modify the existing ruleset with stricter matching criteria, run the ruleset and review the updated results, then adjust as needed until the individuals are matching correctly.
  2. Create and run a new rules fewer matching rules, compare the two rulesets to review and verify the results, and then migrate to the new ruleset once approved.
  3. Create and run a new ruleset with stricter matching criteria, compare the two rulesets to review and verify the results, and then migrate to the new ruleset once approved.
  4. Modify the existing ruleset with stricter matching criteria, compare the two rulesets to review and verify the results, and then migrate to the new ruleset once approved.

Answer(s): C

Explanation:

Identity resolution is the process of linking source profiles from different data sources into unified individual profiles based on match and reconciliation rules. If the identity resolution process is matching individuals that share email addresses or phone numbers, but are not actually the same individual, it means that the match rules are too loose and need to be refined. The best way to address this issue is to create and run a new ruleset with stricter matching criteria, such as adding more attributes or increasing the match score threshold. Then, the consultant can compare the two rulesets to review and verify the results, and see if the new ruleset reduces the false positives and improves the accuracy of the identity resolution. Once the new ruleset is approved, the consultant can migrate to the new ruleset and delete the old one. The other options are incorrect because modifying the existing ruleset can affect the existing unified profiles and cause data loss or inconsistency. Creating and running a new ruleset with fewer matching rules can increase the false negatives and reduce the coverage of the identity resolution.


Reference:

Create Unified Individual Profiles, AI-based Identity Resolution: Linking Diverse Customer Data, Data Cloud Identiy Resolution.



A retail customer wants to bring customer data from different sources and wants to take advantage of identity resolution so that it can be used in segmentation.

On which entity should this be segmented for activation membership?

  1. Subscriber
  2. Unified Individual
  3. Unified Contact
  4. Individual

Answer(s): B

Explanation:

The correct answer is B, Unified Individual. A Unified Individual is a record that represents a customer across different data sources, created by applying identity resolution rulesets. Identity resolution rulesets are sets of match and reconciliation rules that define how to link and merge data from different sources based on common attributes. Data Cloud uses identity resolution rulesets to resolve data across multiple data sources and helps you create one record for each customer, regardless of where the data came from. A retail customer who wants to bring customer data from different sources and use identity resolution for segmentation should segment on the Unified Individual entity, which contains the resolved and consolidated customer data. The other options are incorrect because they do not represent the resolved customer data across different sources. A Subscriber is a record that represents a customer who has opted in to receive marketing communications. A Unified Contact is a record that represents a customer who has a relationship with a specific business unit. An Individual is a record that represents a customer's profile data from a single data source.


Reference:

Identity Resolution Ruleset Processing Results
Consider Data Implications for Segmentation
Prepare for your Salesforce Data Cloud Consultant Credential AI-based Identity Resolution: Linking Diverse Customer Data



A consultant is reviewing a recent activation using engagement-based related attributes but is not seeing any related attributes in their payload for the majority of their segment members.
Which two areas should the consultant review to help troubleshoot this issue? Choose 2 answers

  1. The related engagement events occurred within the last 90 days.
  2. The activations are referencing segments that segment on profile data rather than engagement data.
  3. The correct path is selected for the related attributes.
  4. The activated profiles have a Unified Contact Point.

Answer(s): A,C

Explanation:

Engagement-based related attributes are attributes that describe the interactions of a person with an email message, such as opens, clicks, unsubscribes, etc. These attributes are stored in the Engagement data model object (DMO) and can be added to an activation to send more personalized communications. However, there are some considerations and limitations when using engagement-based related attributes, such as:
For engagement data, activation supports a 90-day lookback window. This means that only the attributes from the engagement events that occurred within the last 90 days are considered for activation. Any records outside of this window are not included in the activation payload. Therefore, the consultant should review the event time of the related engagement events and make sure they are within the lookback window.
The correct path to the related attributes must be selected for the activation. A path is a sequence of DMOs that are connected by relationships in the data model. For example, the path from Individual to Engagement is Individual -> Email -> Engagement. The path determines which related attributes are available for activation and how they are filtered. Therefore, the consultant should review the path selection and make sure it matches the desired related attributes and filters. The other two options are not relevant for this issue. The activations can reference segments that segment on profile data rather than engagement data, as long as the activation target supports related attributes. The activated profiles do not need to have a Unified Contact Point, which is a unique identifier for a person across different data sources, to activate engagement-based related attributes.


Reference:

Add Related Attributes to an Activation, Related Attributes in Data Cloud activation have no values, Explore the Engagement Data Model Object






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