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Salesforce Data-Con-101 Exam Overview:

Certification Vendor:Salesforce
Exam Name:Salesforce Certified Data Cloud Consultant
Exam Number:Data-Con-101
Exam Duration:105 minutes
Available Languages:English
Related Certifications:Salesforce Certified AI Associate
Exam Format:Multiple-choice, Multiple-select
Passing Score:62%
Exam Price:USD 200
Real Exam Qty:60 (plus up to 5 unscored questions)
Certificate Validity Period:Maintenance required annually (Trailhead modules)
Sample Questions:Salesforce Data-Con-101 Sample Questions
Exam Way:Online (Webassessor/PSI) or Onsite (Pearson VUE)
Pre Condition:No hard prerequisites; recommended 2+ years of experience in data strategy and data modeling
Official Syllabus URL:https://trailhead.salesforce.com/credentials/datacloudconsultant

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Salesforce Data-Con-101 Exam Syllabus Topics:

TopicDetails
Topic 1
  • Data Cloud Setup and Administration: This domain focuses on configuring and managing Data Cloud environments through permissions, data streams, data bundles, and data spaces. It also covers administrative tools and techniques for diagnosing and exploring data using reports, dashboards, flows, APIs, and explorer tools.
Topic 2
  • Segmentation and Insights: This domain centers on creating audience segments and deriving analytical insights from Data Cloud. It includes configuring and maintaining segments, analyzing membership scenarios, and distinguishing between calculated insights and real-time streaming insights.
Topic 3
  • Data Cloud Overview: This domain covers the foundational understanding of Data Cloud including its core purpose, terminology, business value, and technical architecture. It also addresses typical use cases and the essential principles of ethical data handling when working with customer data.
Topic 4
  • Identity Resolution: This domain explores creating unified customer profiles through matching and reconciliation processes. It covers how rule sets determine when records link together, how conflicting data is resolved, and understanding the outcomes and use cases of unified identities.

Salesforce Certified Data Cloud Consultant Sample Questions (Q93-Q98):

NEW QUESTION # 93
A company stores customer data in Marketing Cloud and uses the Marketing Cloud Connector to ingest data into Data Cloud.
Where does a request for data deletion or right to be forgotten get submitted?

Answer: C


NEW QUESTION # 94
A company is seeking advice from a consultant on how to address the challenge of having multiple leads and contacts in Salesforce that share the same email address. The consultant wants to provide a detailed and comprehensive explanation on how Data Cloud can be leveraged to effectively solve this issue.
What should the consultant highlight to address this company's business challenge?

Answer: A

Explanation:
Issue Overview: When multiple leads and contacts share the same email address in Salesforce, it can lead to data duplication, inaccurate customer views, and inefficient marketing and sales efforts.
Data Cloud Identity Resolution: Salesforce Data Cloud offers Identity Resolution as a powerful tool to address this issue. It helps in merging and unifying data from multiple sources to create a single, comprehensive customer profile.
Process:
Data Ingestion: Import lead and contact data into Salesforce Data Cloud.
Identity Resolution Rules: Configure Identity Resolution rules to match and merge records based on key identifiers like email addresses.
Unification: The tool consolidates records that share the same email address, eliminating duplicates and ensuring a single view of each customer.
Continuous Updates: As new data comes in, Identity Resolution continuously updates and maintains the unified profiles.
Benefits:
Accurate Customer View: Reduces duplicate records and provides a complete view of each customer's interactions and history.
Improved Efficiency: Streamlines marketing and sales efforts by targeting a unified customer profile.
References:
Salesforce Data Cloud Identity Resolution
Salesforce Help: Identity Resolution Overview


NEW QUESTION # 95
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?

Answer: C

Explanation:
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


NEW QUESTION # 96
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?

Answer: A

Explanation:
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. References: Create a Custom Data Model Object from an Existing Data Model Object, Create a Segment in Data Cloud, Data Model Object Category


NEW QUESTION # 97
Cloud Kicks plans to do a full deletion of one of its existing data streams and its underlying data lake object (DLO).
What should the consultant consider before deleting the data stream?

Answer: C

Explanation:
Data Streams and DLOs: In Salesforce Data Cloud, data streams are used to ingest data, which is then stored in Data Lake Objects (DLOs).
Deletion Considerations: Before deleting a data stream, it's crucial to consider the dependencies and usage of the underlying DLO.
Data Transform Usage:
Impact of Deletion: If the underlying DLO is used in a data transform, deleting the data stream will affect any transforms relying on that DLO.
Dependency Check: Ensure that the DLO is not part of any active data transformations or processes that could be disrupted by its deletion.
References:
Salesforce Data Cloud Documentation: Data Streams
Salesforce Data Cloud Documentation: Data Transforms


NEW QUESTION # 98
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