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Data-Cloud-Consultant Musterprüfungsfragen - Data-Cloud-ConsultantZertifizierung & Data-Cloud-ConsultantTestfagen

Fast2test ist eine erstklassige Website für die Salesforce Data-Cloud-Consultant Zertifzierungsprüfung. Im Fast2test können Sie Tipps und Prüfungsmaterialien finden. Sie können auch die Examensfragen-und antworten teilweise als Probe kostenlos herunterladen. Fast2test kann Ihnen umsonst die Updaets der Prüfungsmaterialien für die Salesforce Data-Cloud-Consultant Prüfung bieten. Alle unseren Zertifizierungsprüfungen enthalten Antworten. Unser Eliteteam von IT-Fachleuten wird die neuesten und richtigen Examensübungen nach ihren fachlichen Erfahrungen bearbeiten, um Ihnen bei der Prüfung zu helfen. Alles in allem, wir werden Ihnen alle einschlägigen Materialien in Bezug auf die Salesforce Data-Cloud-Consultant Zertifizierungsprüfung bieten.

Salesforce Data-Cloud-Consultant Prüfungsplan:

Thema
Einzelheiten

Thema 1

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.

Thema 2

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.

Thema 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.

>> Data-Cloud-Consultant Zertifizierungsfragen <<

Data-Cloud-Consultant Prüfungsmaterialien & Data-Cloud-Consultant Dumps

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Salesforce Certified Data Cloud Consultant Data-Cloud-Consultant Prüfungsfragen mit Lösungen (Q136-Q141):

136. Frage
A customer notices that their consolidation rate has recently increased. They contact the consultant to ask why.
What are two likely explanations for the increase?
Choose 2 answers

A. Duplicates have been removed from source system data streams.
B. Identity resolution rules have been added to the ruleset to increase the number of matched
C. Identity resolution rules have been removed to reduce the number of matched profiles.
D. New data sources have been added to Data Cloud that largely overlap with the existing profiles.

Antwort: B,D

Begründung:
profiles.
Explanation:
The consolidation rate is a metric that measures the amount by which source profiles are combined to produce unified profiles in Data Cloud, calculated as 1 - (number of unified profiles / number of source profiles). A higher consolidation rate means that more source profiles are matched and merged into fewer unified profiles, while a lower consolidation rate means that fewer source profiles are matched and more unified profiles are created. There are two likely explanations for why the consolidation rate has recently increased for a customer:
New data sources have been added to Data Cloud that largely overlap with the existing profiles. This means that the new data sources contain many profiles that are similar or identical to the profiles from the existing data sources. For example, if a customer adds a new CRM system that has the same customer records as their old CRM system, the new data source will overlap with the existing one. When Data Cloud ingests the new data source, it will use the identity resolution ruleset to match and merge the overlapping profiles into unified profiles, resulting in a higher consolidation rate.
Identity resolution rules have been added to the ruleset to increase the number of matched profiles. This means that the customer has modified their identity resolution ruleset to include more match rules or more match criteria that can identify more profiles as belonging to the same individual. For example, if a customer adds a match rule that matches profiles based on email address and phone number, instead of just email address, the ruleset will be able to match more profiles that have the same email address and phone number, resulting in a higher consolidation rate.

A. Individuals who purchased at least one of any red' product and also purchased at least one pair of 'shoes'
B. Individuals who purchased at least one of any 'red' product or purchased at least one pair of
'shoes'
C. Individuals who made a purchase of at least one 'red shoes' and nothing else
D. Individuals who purchased at least one 'red shoes' as a single line item in a purchase

Antwort: A

Begründung:
When creating a segment on an individual, using two separate containers linked by an AND means that the individual must satisfy both the conditions in the containers. In this case, the individual must have purchased at least one product with the color attribute equal to 'red' and at least one product with the primary product category attribute equal to 'shoes'. The products do not have to be the same or purchased in the same transaction. Therefore, the correct answer is A.
The other options are incorrect because they imply different logical operators or conditions. Option B implies that the individual must have purchased a single product that has both the color attribute equal to 'red' and the primary product category attribute equal to 'shoes'. Option C implies that the individual must have purchased only one product that has both the color attribute equal to 'red' and the primary product category attribute equal to 'shoes' and no other products. Option D implies that the individual must have purchased either one product with the color attribute equal to 'red' or one product with the primary product category attribute equal to 'shoes' or both, which is equivalent to using an OR operator instead of an AND operator.
References:
* Create a Container for Segmentation
* Create a Segment in Data Cloud
* Navigate Data Cloud Segmentation

138. Frage
Northern Trail Outfitters (NTO), an outdoor lifestyle clothing brand, recently started a new line of business. The new business specializes in gourmet camping food. For business reasons as well as security reasons, it's important to NTO to keep all Data Cloud data separated by brand.
Which capability best supports NTO's desire to separate its data by brand?

A. Data model objects for each brand
B. Data streams for each brand
C. Data sources for each brand
D. Data spaces for each brand

Antwort: D

Begründung:
Explanation
Data spaces are logical containers that allow you to separate and organize your data by different criteria, such as brand, region, product, or business unit1. Data spaces can help you manage data access, security, and governance, as well as enable cross-cloud data integration and activation2. For NTO, data spaces can support their desire to separate their data by brand, so that they can have different data models, rules, and insights for their outdoor lifestyle clothing and gourmet camping food businesses. Data spaces can also help NTO comply with any data privacy and security regulations that may apply to their different brands3. The other options are incorrect because they do not provide the same level of data separation and organization as data spaces. Data streams are used to ingest data from different sources into Data Cloud, but they do not separate the data by brand4. Data model objects are used to definethe structure and attributes of the data, but they do not isolate the data by brand5. Data sources are used to identify the origin and type of the data, but they do not partition the data by brand. References: Data Spaces Overview, Create Data Spaces, Data Privacy and Security in Data Cloud, Data Streams Overview, Data Model Objects Overview, [Data Sources Overview]

139. Frage
The Salesforce CRM Connector is configured and the Case object data stream is set up. Subsequently, a new custom field named Business Priority is created on the Case object in Salesforce CRM. However, the new field is not available when trying to add it to the data stream.
Which statement addresses the cause of this issue?

A. The Salesforce Data Loader application should beused to perform a bulk upload from a desktop.
B. Customfields on the Case object are not supportedfor ingesting into Data Cloud.
C. The Salesforce Integration User Is missing Rad permissions on the newly created field.
D. After 24 hourswhen the data stream refreshesit will automatically include any new fields that were added to the Salesforce CRM.

Antwort: C

Begründung:
Explanation
The Salesforce CRM Connector uses the Salesforce Integration User to access the data from the Salesforce CRM org. The Integration User must have the Read permission on the fields that are included in the data stream. If the Integration User does not have the Read permission on the newly created field, the field will not be available for selection in the data stream configuration. To resolve this issue, the administrator should assign the Read permission on the new field to the Integration User profile or permission set. References: Create a Salesforce CRM Data Stream, Edit a Data Stream, Salesforce Data Cloud Full Refresh for CRM, SFMC, or Ingestion API Data Streams

140. Frage
What is the result of a segmentation criteria filtering on City | Is Equal To | 'San Jose'?

A. Cities containing 'San Jose', 'San Jose', '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 only containing 'San Jose' or 'San Jose'

Antwort: B

Begründung:
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. Reference: Segmentation Criteria, Segmentation Operators

141. Frage
......

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Data-Cloud-Consultant Prüfungsmaterialien: https://de.fast2test.com/Data-Cloud-Consultant-premium-file.html

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