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CRM-Analytics-and-Einstein-Discovery-Consultant資格関連題 & CRM-Analytics-and-Einstein-Discovery-Consultant日本語受験教科書

CertJukenのSalesforceのCRM-Analytics-and-Einstein-Discovery-Consultant試験トレーニング資料は高度に認証されたIT領域の専門家の経験と創造を含めているものです。私たちのIT専門家は受験生のために、最新的なSalesforceのCRM-Analytics-and-Einstein-Discovery-Consultant問題集を提供します。うちの学習教材の高い正確性は言うまでもありません。受験生が最も早い時間で、一回だけでSalesforceのCRM-Analytics-and-Einstein-Discovery-Consultant認定試験に合格できるために、CertJukenはずっとがんばります。

Salesforce CRM-Analytics-and-Einstein-Discovery-Consultant 認定試験の出題範囲：

トピック
出題範囲

トピック 1

Analytics Dashboard Implementation: Here, consultants embark on a creative exploration of dashboard configuration, optimization of query performance using Dashboard Inspector, and using advanced functionality such as windowing.

トピック 2

Analytics Dashboard Design: Building upon the design foundation, this section challenges candidates to bring their dashboard designs to life. It covers the technical expertise required to scope, validate, and prioritize dashboard design requirements.

トピック 3

Einstein Discovery: This section unveils the magic of AI-driven insights and candidates' ability to analyze and choose one of the three types of predictions. It involves leveraging Einstein's advanced analytics capabilities to adjust data parameters, add or remove data and columns for the improvement of the model.

トピック 4

Data Layer: In this comprehensive section, Salesforce consultants delve into the heart of data extraction and loading. It's all about showcasing a deep understanding of implementing refreshes for data syncs, performing data transformations, and implementing delivery management strategies in dataflows.

>> CRM-Analytics-and-Einstein-Discovery-Consultant資格関連題 <<

CRM-Analytics-and-Einstein-Discovery-Consultant テストエンジ、CRM-Analytics-and-Einstein-Discovery-Consultant勉強資料、Salesforce Certified CRM Analytics and Einstein Discovery Consultant 練習問題

誰もが良い仕事とまともな収入を望んでいます。しかし、彼らが優れた能力と優れた主要な知識を持っていない場合、彼らはまともな仕事を見つけるのは難しいです。テストCRM-Analytics-and-Einstein-Discovery-Consultant認定に合格すると、夢を実現し、満足のいく仕事を見つけることができます。 CRM-Analytics-and-Einstein-Discovery-Consultant学習教材は、CRM-Analytics-and-Einstein-Discovery-Consultant試験に簡単に合格するのに役立つ優れたツールです。時間をかけて学習する必要はありません。 CRM-Analytics-and-Einstein-Discovery-Consultant試験ガイドは高品質であり、当社の製品を使用する場合、CRM-Analytics-and-Einstein-Discovery-Consultant試験に合格する可能性は99％〜100％と非常に高くなっています。

Salesforce Certified CRM Analytics and Einstein Discovery Consultant 認定 CRM-Analytics-and-Einstein-Discovery-Consultant 試験問題 (Q57-Q62):

質問 # 57
A company realizes it has a lot of rich information around its cases, but unfortunately, most of this is unstructured/textual dat a. The company is exploring how to include some of this information in its case prioritization.
Which option within CRM Analytics should a consultant leverage?

A. Bucket transformation in Recipes
B. Detect Sentiment transformation in Recipes
C. Cluster transformation in Recipes

正解：B

解説：
For a company with a wealth of unstructured textual data in their cases, the "Detect Sentiment" transformation within CRM Analytics Recipes is a crucial tool. This transformation analyzes the sentiment of the text data-whether it's positive, neutral, or negative-and this insight can be highly valuable in case prioritization processes. Here's why this transformation is useful:
Insight into Customer Sentiments: By detecting sentiment, the company can prioritize cases based on the urgency and emotional tone expressed in the text, which might indicate customer dissatisfaction or urgency.
Automation and Efficiency: Automatically categorizing cases based on sentiment can streamline workflows and ensure that critical cases are handled promptly.
Enhanced Customer Service: Responding to negative sentiments swiftly can improve customer satisfaction and potentially mitigate issues before they escalate.

質問 # 58
When Analytics runs a dataflow that accesses Salesforce objects, which user does it use?

A. The current user
B. The record owner
C. The Integration User
D. The system administrator

正解：C

質問 # 59
How many groupings can you have in a Compare Table?

A. Infinite
B. Up to four
C. None
D. One

正解：B

質問 # 60
A consultant built an Einstein Analytics app for the Sales Operations team. The Sales Operations team wants to share their app with other people at the company. The consultant recommends distributing the app as an Einstein Analytics template app.
A set of JSON files will be generated after a template is created from the Sales Operations app. What is the name of the JSON file that manages template metadata and all other template elements'

A. ui.json
B. template-info.json
C. aster- info.j son
D. template-to-app-rules.json

正解：B

質問 # 61
Universal Containers (UC) is rolling out CRM Analytics to its field sales that include dashboards withorder data from an external source.
UC has a well-defined role hierarchy where everyone is assigned to an appropriate node on the hierarchy. In addition, the order data has a reference to a Salesforce opportunity.
An individual sales rep should be able to view all orders that they own or as part of the account team or opportunity team. The sales manager should be able to view all orders for the entire sales team. Similarly, the VP of sales should be able to view orders for everyone who rolls up in that hierarchy.
The dataset has a field called Ownerld which represents the order owner.
Given this information, how should a CRM Analytics consultant implement the above requirements?

A. As part of the recipe, use the flatten operation on the role hierarchy, create a multi-value attribute called 'ParentRoleIDs' on the dataset, and apply the following security predicate: 'ParentRoleIDs' == "$User.UserRoleld" || 'TeamMember.Id' '$User, Id" || 'Ownerld' == "$User.Id".
B. As part of the recipe, use a multi row formula on the Roleld field to create an attribute called 'ParentRoleIDs' on the dataset, and apply the following security predicate: "$User.UserRoleld" || 'Ownerld' == "$User.Id".
C. As part of the recipe, use a formula on the Roleid fild to create an attribute called 'ParentRolelDs' on the dataset, and apply the following security predicate: 'ParentRolelDs' == ''$UserRoleId'' || Owned == '$User,id,

正解：A

解説：
In addressing the requirements of Universal Containers to ensure proper visibility of order data across different levels of the sales hierarchy, the use of a security predicate based on role hierarchies is paramount. Here's why Option B is the ideal approach:
Flatten Operation on Role Hierarchy: This operation is essential as it allows for the creation of a simplified or "flattened" view of the hierarchical relationships within the organization. This flattened view enables the dataset to understand and respect the hierarchical structure in security implementations.
Creating a Multi-value Attribute ('ParentRoleIDs'): By creating this attribute, the recipe can hold multiple role IDs that a particular user has visibility permissions for. This is crucial in a hierarchical organization like UC where data visibility needs to cascade down the hierarchy.
Security Predicate: The predicate ('ParentRoleIDs' == "$User.UserRoleld" || 'TeamMember.Id' == '$User.Id' || 'Ownerld' == "$User.Id") effectively enforces that:
A user can see all orders where their role matches any of the role IDs in the 'ParentRoleIDs' list (hierarchical visibility).
A user can see all orders where they are specifically listed as a team member.
A user can see all orders where they are the owner.
This approach aligns with best practices for implementing row-level security in CRM Analytics, ensuring data visibility is managed correctly according to the defined organizational hierarchy and individual data ownership.

質問 # 62
......

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