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Salesforce Data-Cloud-Consultant Valid Test Dumps, Data-Cloud-Consultant Latest Exam Format
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Salesforce Data-Cloud-Consultant Exam Syllabus Topics:
Topic
Details
Topic 1
- Act on Data: This topic defines activations and their basic use cases, using attributes and related attributes, identifying and analyzing timing dependencies affecting the Data Cloud lifecycle. Additionally it focuses on troubleshooting common problems with activations, and using data actions, including their requirements and intended use cases.
Topic 2
- 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.
Topic 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.
Topic 4
- 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.
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Salesforce Certified Data Cloud Consultant Sample Questions (Q34-Q39):
NEW QUESTION # 34
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?
- A. Calculated Insights
- B. Data Bundles
- C. Identity Resolution
- D. Identity Resolution
Answer: C
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 # 35
A consultant is discussing the benefits of Data Cloud with a customer that has multiple disjointed data sources.
Which two functional areas should the consultant highlight in relation to managing customer data?
Choose 2 answers
- A. Master Data Management
- B. Unified Profiles
- C. Data Harmonization
- D. Data Marketplace
Answer: B,C
Explanation:
Explanation
Data Cloud is an open and extensible data platform that enables smarter, more efficient AI with secure access to first-party and industry data1. Two functional areas that the consultant should highlight in relation to managing customer data are:
* Data Harmonization: Data Cloud harmonizes data from multiple sources and formats into a common schema, enabling a single source of truth for customer data1. Data Cloud also applies data quality rules and transformations to ensure data accuracy and consistency.
* Unified Profiles: Data Cloud creates unified profiles of customers and prospects by linking data across different identifiers, such as email, phone, cookie, and device ID1. Unified profiles providea holistic view of customer behavior, preferences, and interactions across channels and touchpoints. The other options are not correct because:
* Master Data Management: Master Data Management (MDM) is a process of creating and maintaining a single, consistent, and trusted source of master data, such as product, customer, supplier, or location data. Data Cloud does not provide MDM functionality, but it can integrate with MDM solutions to enrich customer data.
* Data Marketplace: Data Marketplace is a feature of Data Cloud that allows users to discover, access, and activate data from third-party providers, such as demographic, behavioral, and intent data. Data Marketplace is not a functional area related to managing customer data, but rather a source of external data that can enhance customer data. References:
* Salesforce Data Cloud
* [Data Harmonization for Data Cloud]
* [Unified Profiles for Data Cloud]
* [What is Master Data Management?]
* [Integrate Data Cloud with Master Data Management]
* [Data Marketplace for Data Cloud]
NEW QUESTION # 36
A company wants to test its marketing campaigns with different target populations.
What should the consultant adjust in the Segment Canvas interface to get different populations?
- A. Segmentation filters, direct attributions, and data sources
- B. Direct attributes and related attributes
- C. Population filters and direct attributes
- D. Direct attributes, related attributes, and population filters
Answer: D
Explanation:
* Segmentation in Salesforce Data Cloud:
The Segment Canvas interface is used to define and adjust target populations for marketing campaigns.
Reference:
* Elements for Adjusting Target Populations:
Direct Attributes: These are specific attributes directly related to the target entity (e.g., customer age, location).
Related Attributes: These are attributes related to other entities connected to the target entity (e.g., purchase history).
Population Filters: Filters applied to define and narrow down the segment population (e.g., active customers).
* Steps to Adjust Populations in Segment Canvas:
Direct Attributes: Select attributes that directly describe the target population.
Related Attributes: Incorporate attributes from related entities to enrich the segment criteria.
Population Filters: Apply filters to refine and target specific subsets of the population.
Example: To create a segment of "Active Customers Aged 25-35," use age as a direct attribute, purchase activity as a related attribute, and apply population filters for activity status and age range.
* Practical Application:
Navigate to the Segment Canvas.
Adjust direct attributes and related attributes based on campaign goals.
Apply population filters to fine-tune the target audience.
NEW QUESTION # 37
A customer has a requirement to be able to view the last time each segment was published within their Data Cloud org.
Which two features should the consultant recommend to best address this requirement?
Choose 2 answers
- A. Profile Explorer
- B. Calculated insight
- C. Report
- D. Dashboard
Answer: C,D
Explanation:
Explanation
A customer who wants to view the last time each segment was published within their Data Cloud org can use the dashboard and report features to achieve this requirement. A dashboard is a visual representation of data that can show key metrics, trends, and comparisons. A report is a tabular or matrix view of data that can show details, summaries, and calculations. Both dashboard and report features allow the user to create, customize, and share data views based on their needs and preferences. To view the last time each segment was published, the user can create a dashboard or a report that shows the segment name, the publish date, and the publish status fields from the segment object. The user can also filter, sort, group, or chart the data by these fields to get more insights and analysis. The user can also schedule, refresh, or export the dashboard or report data as needed. References: Dashboards, Reports
NEW QUESTION # 38
A healthcare client wants to make use of identity resolution, but does not want to risk unifying profiles that may share certain personally identifying information (PII).
Which matching rule criteria should a consultant recommend for the most accurate matching results?
- A. Exact Last Name and Emil
- B. Email Address and Phone
- C. Fuzzy First Name, Exact Last Name, and Email
- D. Party Identification on Patient ID
Answer: D
Explanation:
Identity resolution is the process of linking data from different sources into a unified profile of a customer or an individual. Identity resolution uses matching rules to compare the attributes of different records and determine if they belong to the same person. Matching rules can be based on exact or fuzzy matching of various attributes, such as name, email, phone, address, or custom identifiers. A healthcare client who wants to use identity resolution, but does not want to risk unifying profiles that may share certain personally identifying information (PII), such as name or email, should use a matching rule criteria that is based on a unique and reliable identifier that is specific to the healthcare domain. One such identifier is the patient ID, which is a unique number assigned to each patient by a healthcare provider or system. By using the party identification on patient ID as a matching rule criteria, the healthcare client can ensure that only records that have the same patient ID are matched and unified, and avoid false positives or false negatives that may occur due to common or similar names or emails. The party identification on patient ID is also a secure and compliant way of handling sensitive healthcare data, as it does not expose or share any PII that may be subject to data protection regulations or standards. References: Configure Identity Resolution Rulesets, A framework of identity resolution: evaluating identity attributes and methods
NEW QUESTION # 39
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