그 외, PassTIP Data-Con-101 시험 문제집 일부가 지금은 무료입니다: https://drive.google.com/open?id=1h6r2lS6R_0D8KgqHeAo8sDbuDWAXWTSd
PassTIP의 제품을 구매하시면 우리는 일년무료업데이트 서비스를 제공함으로 여러분을 인증시험을 패스하게 도와줍니다. 만약 인증시험내용이 변경이 되면 우리는 바로 여러분들에게 알려드립니다.그리고 최신버전이 있다면 바로 여러분들한테 보내드립니다. PassTIP는 한번에Salesforce Data-Con-101인증시험을 패스를 보장합니다.
| 주제 | 소개 |
|---|---|
| 주제 1 |
|
| 주제 2 |
|
| 주제 3 |
|
| 주제 4 |
|
많은 분들이Salesforce Data-Con-101시험을 패스하려고 하는데 시험대비방법을 찾지 못하고 계십니다. Salesforce Data-Con-101덤프를 구매하려면 먼저Salesforce Data-Con-101샘플문제를 다운받아 덤프품질을 검증후 주문하시면 믿음이 생길것입니다. Salesforce Data-Con-101시험대비덤프는 IT업계에 오랜 시간동안 종사한 전문가들의 노하우로 연구해낸 최고의 자료입니다.
질문 # 28
A customer has a Master Customer table from their CRM to ingest into Data Cloud. The table contains a name and primary email address, along with other personally Identifiable information (Pll).
How should the fields be mapped to support identity resolution?
정답：C
설명：
To support identity resolution in Data Cloud, the fields from the Master Customer table should be mapped to the standard data model objects that are designed for this purpose. The Individual object is used to store the name and other personally identifiable information (PII) of a customer, while the Contact Phone Email object is used to store the primary email address and other contact information of a customer. These objects are linked by a relationship field that indicates the contact information belongs to the individual. By mapping the fields to these objects, Data Cloud can use the identity resolution rules to match and reconcile the profiles from different sources based on the name and email address fields. The other options are not recommended because they either create a new custom object that is not part of the standard data model, or map all fields to the Customer object that is not intended for identity resolution, or map all fields to the Individual object that does not have a standard email address field. References: Data Modeling Requirements for Identity Resolution, Create Unified Individual Profiles
질문 # 29
Which two common use cases can be addressed with Data Cloud?
Choose 2 answers
정답：A,B
설명：
Data Cloud is a data platform that can help customers connect, prepare, harmonize, unify, query, analyze, and act on their data across various Salesforce and external sources. Some of the common use cases that can be addressed with Data Cloud are:
Understand and act upon customer data to drive more relevant experiences. Data Cloud can help customers gain a 360-degree view of their customers by unifying data from different sources and resolving identities across channels. Data Cloud can also help customers segment their audiences, create personalized experiences, and activate data in any channel using insights and AI.
Harmonize data from multiple sources with a standardized and extendable data model. Data Cloud can help customers transform and cleanse their data before using it, and map it to a common data model that can be extended and customized. Data Cloud can also help customers create calculated insights and related attributes to enrich their data and optimize identity resolution.
The other two options are not common use cases for Data Cloud. Data Cloud does not provide data governance or backup and disaster recovery features, as these are typically handled by other Salesforce or external solutions.
Learn How Data Cloud Works
About Salesforce Data Cloud
Discover Use Cases for the Platform
Understand Common Data Analysis Use Cases
질문 # 30
An organization wants to enable users with the ability to identify and select text attributes from a picklist of options.
Which Data Cloud feature should help with this use case?
정답：A
설명：
Value suggestion is a Data Cloud feature that allows users to see and select the possible values for a text field when creating segment filters. Value suggestion can be enabled or disabled for each data model object (DMO) field in the DMO record home. Value suggestion can help users to identify and select text attributes from a picklist of options, without having to type or remember the exact values. Value suggestion can also reduce errors and improve data quality by ensuring consistent and valid values for the segment filters. References: Use Value Suggestions in Segmentation, Considerations for Selecting Related Attributes
질문 # 31
Northern Trail Outfitters (NTO) owns and operates six unique brands, each with their own set of customers, transactions, and loyalty information. The marketing director wants to ensure that segments and activations from the NTO Outlet brand do not reference customers or transactions from the other brands.
What is the most efficient approach to handle this requirement?
정답：C
설명：
To ensure segments and activations for the NTO Outlet brand do not reference data from other brands, the most efficient approach is to isolate the Outlet brand's data using Data Spaces. Here's the analysis:
Data Spaces (Option B):
Definition: Data Spaces in Salesforce Data Cloud partition data into isolated environments, ensuring that segments, activations, and analytics only reference data within the same space.
Why It Works: By creating a dedicated Data Space for the Outlet brand, all customer, transaction, and loyalty data for Outlet will be siloed. Segments and activations built in this space cannot access data from other brands, even if they exist in the same Data Cloud instance.
Efficiency: This avoids complex filtering logic or manual data management. It aligns with Salesforce's best practice of using Data Spaces for multi-brand or multi-entity organizations (Source: Salesforce Data Cloud Implementation Guide, "Data Partitioning with Data Spaces").
Why Other Options Are Incorrect:
Business Unit Aware Activation (A):
Business Unit (BU) settings in Salesforce CRM control record visibility but are not natively tied to Data Cloud segmentation.
BU-aware activation ensures activations respect sharing rules but does not prevent segments from referencing data across BUs in Data Cloud.
Six Different Data Spaces (C):
While creating a Data Space for each brand (6 total) would technically isolate all data, the requirement specifically focuses on the Outlet brand. Creating six spaces is unnecessary overhead and not the "most efficient" solution.
Batch Data Transform to Generate DLO (D):
Creating a Data Lake Object (DLO) via batch transforms would require ongoing manual effort to filter Outlet- specific data and does not inherently prevent cross-brand references in segments.
Steps to Implement:
Step 1: Navigate to Data Cloud Setup > Data Spaces and create a new Data Space for the Outlet brand.
Step 2: Ingest Outlet-specific data (customers, transactions, loyalty) into this Data Space.
Step 3: Build segments and activations within the Outlet Data Space. The system will automatically restrict access to other brands' data.
Conclusion: Separating the Outlet brand into its own Data Space (Option B) is the most efficient way to enforce data isolation and meet the requirement. This approach leverages native Data Cloud functionality without overcomplicating the setup.
질문 # 32
A consultant wants to confirm the Identity resolution they Just set up. Which two features can the consultant use to validate the data on a unified profile?
Choose 2 answers
정답：A,C
설명：
To validate the data on a unified profile after setting up identity resolution, the consultant can use Data Explorer and the Query API . Here's why:
Understanding Identity Resolution Validation
Identity resolution combines data from multiple sources into a unified profile.
Validating the unified profile ensures that the resolution process is working correctly and that the data is accurate.
Why Data Explorer and Query API?
Data Explorer :
Data Explorer is a built-in tool in Salesforce Data Cloud that allows users to view and analyze unified profiles.
It provides a detailed view of individual profiles, including resolved identities and associated attributes.
Query API :
The Query API enables programmatic access to unified profiles and related data.
Consultants can use the API to query specific profiles and validate the results of identity resolution programmatically.
Other Options Are Less Suitable :
A). Identity Resolution : This refers to the process itself, not a tool for validation.
B). Data Actions : Data actions are used to trigger workflows or integrations, not for validating unified profiles.
Steps to Validate Unified Profiles
Using Data Explorer :
Navigate to Data Cloud > Data Explorer .
Search for a specific profile and review its resolved identities and attributes.
Verify that the data aligns with expectations based on the identity resolution rules.
Using Query API :
Use the Query API to retrieve unified profiles programmatically.
Compare the results with expected outcomes to confirm accuracy.
Conclusion
The consultant should use Data Explorer and the Query API to validate the data on unified profiles, ensuring that identity resolution is functioning as intended.
질문 # 33
......
Salesforce인증Data-Con-101시험을 패스하여 자격증을 취득한다면 여러분의 미래에 많은 도움이 될 것입니다.Salesforce인증Data-Con-101시험자격증은 it업계에서도 아주 인지도가 높고 또한 알아주는 시험이며 자격증 하나로도 취직은 문제없다고 볼만큼 가치가 있는 자격증이죠.Salesforce인증Data-Con-101시험은 여러분이 it지식테스트시험입니다.
Data-Con-101최신 업데이트버전 덤프문제공부: https://www.passtip.net/Data-Con-101-pass-exam.html
참고: PassTIP에서 Google Drive로 공유하는 무료, 최신 Data-Con-101 시험 문제집이 있습니다: https://drive.google.com/open?id=1h6r2lS6R_0D8KgqHeAo8sDbuDWAXWTSd