BOOK DATA-CLOUD-CONSULTANT FREE & DATA-CLOUD-CONSULTANT RELIABLE TEST REVIEW

Book Data-Cloud-Consultant Free & Data-Cloud-Consultant Reliable Test Review

Book Data-Cloud-Consultant Free & Data-Cloud-Consultant Reliable Test Review

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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
  • 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
  • Data Cloud Overview: This topic covers Data Cloud's function, key terminology, business value, typical use cases, the Data Cloud lifecycle, dependencies, and principles of data ethics. These sub-topics provide an overview of Data Cloud's capabilities and applications.

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Salesforce Certified Data Cloud Consultant Sample Questions (Q103-Q108):

NEW QUESTION # 103
What does the Ignore Empty Value option do in identity resolution?

  • A. Ignores Individual object records with empty fields when running identity resolution rules
  • B. Ignores empty fields when running any custom match rules
  • C. Ignores empty fields when running reconciliation rules
  • D. Ignores empty fields when running the standard match rules

Answer: C

Explanation:
Explanation
The Ignore Empty Value option in identity resolution allows customers to ignore empty fields when running reconciliation rules. Reconciliation rules are used to determine the final value of an attribute for a unified individual profile, based on the values from different sources. The Ignore Empty Value option can be set to true or false for each attribute in a reconciliation rule. If set to true, the reconciliation rule will skip any source that has an empty value for that attribute and move on to the next source in the priority order. If set to false, the reconciliation rule will consider any source that has an empty value for that attribute as a valid source and use it to populate the attribute value for the unified individual profile.
The other options are not correct descriptions of what the Ignore Empty Value option does in identity resolution. The Ignore Empty Value option does not affect the custom match rules or the standard match rules, which are used to identify and link individuals across different sources based on their attributes. The Ignore Empty Value option also does not ignore individual object records with empty fields when running identity resolution rules, as identity resolution rules operate on the attribute level, not the record level.
References:
* Data Cloud Identity Resolution Reconciliation Rule Input
* Configure Identity Resolution Rulesets
* Data and Identity in Data Cloud


NEW QUESTION # 104
What does the Source Sequence reconciliation rule do in identity resolution?

  • A. Identifies which data sources should be used in the process of reconcillation by prioritizing the most recently updated data source
  • B. Includes data from sources where the data is most frequently occurring
  • C. Identifies which individual records should be merged into a unified profile by setting a priority for specific data sources
  • D. Sets the priority of specific data sources when building attributes in a unified profile, such as a first or last name

Answer: D

Explanation:
Explanation
The Source Sequence reconciliation rule sets the priority of specific data sources when building attributes in a unified profile, such as a first or last name. This rule allows you to define which data source should be used as the primary source of truth for each attribute, and which data sources should be used as fallbacks in case the primary source is missing or invalid. For example, you can set the Source Sequence rule to use data from Salesforce CRM as the first priority, data from Marketing Cloud as the second priority, and data from Google Analytics as the third priority for the first name attribute. This way, the unified profile will use the first name value from Salesforce CRM if it exists, otherwise it will use the value from Marketing Cloud, and so on. This rule helps you to ensure the accuracy and consistency of the unified profile attributes across different data sources. References: Salesforce Data Cloud Consultant Exam Guide, Identity Resolution, Reconciliation Rules


NEW QUESTION # 105
Cumulus Financial segregates its sales CRM data based on Region for its Data Cloud users. Multiple data spaces are configured: a default space and two additional spaces tailored for EMEA and APAC regions.
EME A sales reps who need temporary access to visualize data for both regions say that they cannot visualize APAC dat a. APAC sales reps can visualize the corresponding segmented data.
Which statement describes the cause of this issue?

  • A. The APAC data space is not associated with any permission set.
  • B. The EMEA sales reps have not been assigned to the profile associated with the APAC data space.
  • C. The EMEA sales reps have not been assigned to the permission set associated with the APAC data space.
  • D. The APAC data space Is not associated with any profile.

Answer: C


NEW QUESTION # 106
What is the result of a segmentation criteria filtering on City | Is Equal To | 'San Jose'?

  • A. Cities only containing 'San Jose' or 'san jose'
  • B. Cities only containing 'San Jose' or 'San Jose'
  • C. Cities only containing 'San Jose' or 'san jose'
  • D. Cities containing 'San Jose', 'San Jose', 'san jose', or 'san jose'

Answer: A

Explanation:
The result of a segmentation criteria filtering on City | Is Equal To | 'San Jose' is cities only containing 'San Jose' or 'san jose'. This is because the segmentation criteria is case-sensitive and accent-sensitive, meaning that it will only match the exact value that is entered in the filter1. Therefore, cities containing 'San Jose', 'san jose', or 'San Jose' will not be included in the result, as they do not match the filter value exactly. To include cities with different variations of the name 'San Jose', you would need to use the OR operator and add multiple filter values, such as 'San Jose' OR 'San Jose' OR 'san jose' OR 'san jose'2. References: Segmentation Criteria, Segmentation Operators


NEW QUESTION # 107
Which information is provided in a .csv file when activating to Amazon S3?

  • A. The manifest of origin sources within Data Cloud
  • B. The metadata regarding the segment definition
  • C. An audit log showing the user who activated the segment and when it was activated
  • D. The activated data payload

Answer: D

Explanation:
When activating to Amazon S3, the information that is provided in a .csv file is the activated data payload. The activated data payload is the data that is sent from Data Cloud to the activation target, which in this case is an Amazon S3 bucket1. The activated data payload contains the attributes and values of the individuals or entities that are included in the segment that is being activated2. The activated data payload can be used for various purposes, such as marketing, sales, service, or analytics3. The other options are incorrect because they are not provided in a .csv file when activating to Amazon S3. Option A is incorrect because an audit log is not provided in a .csv file, but it can be viewed in the Data Cloud UI under the Activation History tab4. Option C is incorrect because the metadata regarding the segment definition is not provided in a .csv file, but it can be viewed in the Data Cloud UI under the Segmentation tab5. Option D is incorrect because the manifest of origin sources within Data Cloud is not provided in a .csv file, but it can be viewed in the Data Cloud UI under the Data Sources tab. References: Data Activation Overview, Create and Activate Segments in Data Cloud, Data Activation Use Cases, View Activation History, Segmentation Overview, [Data Sources Overview]


NEW QUESTION # 108
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