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Salesforce인증Data-Cloud-Consultant시험은 국제적으로 승인해주는 IT인증시험의 한과목입니다. 근 몇년간 IT인사들에게 최고의 인기를 누리고 있는 과목으로서 그 난이도 또한 높습니다. 자격증을 취득하여 직장에서 혹은 IT업계에서 자시만의 위치를 찾으련다면 자격증 취득이 필수입니다. Salesforce인증Data-Cloud-Consultant시험을 패스하고 싶은 분들은ITDumpsKR제품으로 가보세요.

Salesforce Data-Cloud-Consultant 시험요강:

주제
소개

주제 1

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.

주제 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.

주제 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.

>> Data-Cloud-Consultant인기자격증 덤프문제 <<

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최신 Salesforce Data Cloud Data-Cloud-Consultant 무료샘플문제 (Q155-Q160):

질문 # 155
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?

A. The team member in the Pacific time zone.
B. Neither team member; Data Cloud shows all schedules in GMT.
C. Both team members; Data Cloud adjusts the segment and activation schedules to the time zone of the logged-in user
D. The team member in the Eastern time zone.

정답：C

설명：
The correct answer is D, both team members; Data Cloud adjusts the segment and activation schedules to the time zone of the logged-in user. Data Cloud uses the time zone settings of the logged-in user to display the segment and activation schedules. This means that each user will see the schedules in their own home time zone, regardless of the org time zone setting or the location of other team members. This feature helps users to avoid confusion and errors when scheduling segments and activations across different time zones. The other options are incorrect because they do not reflect how Data Cloud handles time zones. The team member in the Pacific time zone will not see the same time zone as the org time zone setting, unless their personal time zone setting matches the org time zone setting. The team member in the Eastern time zone will not see the schedules in the org time zone setting, unless their personal time zone setting matches the org time zone setting. Data Cloud does not show all schedules in GMT, but rather in the user's local time zone. Reference:
Data Cloud Time Zones
Change default time zones for Users and the organization
Change your time zone settings in Salesforce, Google & Outlook
DateTime field and Time Zone Settings in Salesforce

질문 # 156
Which two dependencies prevent a data stream from being deleted?
Choose 2 answers

A. The underlying data lake object is mapped to a data model object.
B. The underlying data lake object is used in segmentation.
C. The underlying data lake object is used in activation.
D. The underlying data lake object is used in a data transform.

정답：A,D

설명：
To delete a data stream in Data Cloud, the underlying data lake object (DLO) must not have any dependencies or references to other objects or processes. The following two dependencies prevent a data stream from being deleted1:
Data transform: This is a process that transforms the ingested data into a standardized format and structure for the data model. A data transform can use one or more DLOs as input or output. If a DLO is used in a data transform, it cannot be deleted until the data transform is removed or modified2.
Data model object: This is an object that represents a type of entity or relationship in the data model. A data model object can be mapped to one or more DLOs to define its attributes and values. If a DLO is mapped to a data model object, it cannot be deleted until the mapping is removed or changed3.
1: Delete a Data Stream article on Salesforce Help
2: [Data Transforms in Data Cloud] unit on Trailhead
3: [Data Model in Data Cloud] unit on Trailhead

질문 # 157
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

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

정답：A,D

설명：
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 Cloud1. 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 ruleset1. 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 Cloud1. 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 Cloud1. References: Delete an Identity Resolution Ruleset

질문 # 158
A user is not seeing suggested values from newly-modeled data when building a segment.
What is causing this issue?

A. Value suggestion is still processing and to be available.
B. Value suggestion will only return result for the first 50 values of a specific attribute.
C. Value suggestion requires Data Aware Specialist permissions at a minimum.
D. Value suggestion can only work on direct attributes and not related attributes.

정답：A

설명：
Explanation
Value suggestion is a feature that allows users to see suggested values for data model object (DMO) fields when creating segment filters. However, this feature can take up to 24 hours to process and display the values for newly-modeled data. Therefore, if a user is not seeing suggested values from newly-modeled data, it is likely that the value suggestion is still processing and will be available soon. The other options are incorrect because value suggestion does not require any specific permissions, can work on both direct and related attributes, and can return more than 50 values for a specific attribute, depending on the data type and frequency of the values. References: Use Value Suggestions in Segmentation, Data Cloud Limits and Guidelines

질문 # 159
A Data Cloud consultant recently added a new data source and mapped some of the data to a new custom data model object (DMO) that they want to use for creating segments. However, they cannot view the newly created DMO when trying to create a new segment.
What is the cause of this issue?

A. Segmentation is only supported for the Individual and Unified Individual DMOs.
B. The new DMO does not have a relationship to the individual DMO
C. The new DMO is not of category Profile.
D. Data has not yes been ingested into the DMO.

정답：C

설명：
The cause of this issue is that the new custom data model object (DMO) is not of category Profile. A category is a property of a DMO that defines its purpose and functionality in Data Cloud. There are three categories of DMOs: Profile, Event, and Other. Profile DMOs are used to store attributes of individuals or entities, such as name, email, address, etc. Event DMOs are used to store actions or interactions of individuals or entities, such as purchases, clicks, visits, etc. Other DMOs are used to store any other type of data that does not fit into the Profile or Event categories, such as products, locations, categories, etc. Only Profile DMOs can be used for creating segments in Data Cloud, as segments are based on the attributes of individuals or entities. Therefore, if the new custom DMO is not of category Profile, it will not appear in the segmentation canvas. The other options are not correct because they are not the cause of this issue. Data ingestion is not a prerequisite for creating segments, as segments can be created based on the data model schema without actual data. The new DMO does not need to have a relationship to the individual DMO, as segments can be created based on any Profile DMO, regardless of its relationship to other DMOs. Segmentation is not only supported for the Individual and Unified Individual DMOs, as segments can be created based on any Profile DMO, including custom ones. Reference: Create a Custom Data Model Object from an Existing Data Model Object, Create a Segment in Data Cloud, Data Model Object Category

질문 # 160
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