Salesforce Salesforce Certifications DATA-CLOUD-CONSULTANT Questions & Answers

• Question 61:

  A customer notices that their consolidation rate has recently increased. They contact the consultant to ask why.

  What are two likely explanations for the increase?

  Choose 2 answers

  A. New data sources have been added to Data Cloud that largely overlap with the existing profiles.

  B. Duplicates have been removed from source system data streams.

  C. Identity resolution rules have been removed to reduce the number of matched profiles.

  D. Identity resolution rules have been added to the ruleset to increase the number of matched profiles.

  Correct Answer: AD

  The consolidation rate is a metric that measures the amount by which source profiles are combined to produce unified profiles in Data Cloud, calculated as 1 - (number of unified profiles / number of source profiles). A higher consolidation rate means that more source profiles are matched and merged into fewer unified profiles, while a lower consolidation rate means that fewer source profiles are matched and more unified profiles are created. There are two likely explanations for why the consolidation rate has recently increased for a customer: New data sources have been added to Data Cloud that largely overlap with the existing profiles. This means that the new data sources contain many profiles that are similar or identical to the profiles from the existing data sources. For example, if a customer adds a new CRM system that has the same customer records as their old CRM system, the new data source will overlap with the existing one. When Data Cloud ingests the new data source, it will use the identity resolution ruleset to match and merge the overlapping profiles into unified profiles, resulting in a higher consolidation rate. Identity resolution rules have been added to the ruleset to increase the number of matched profiles. This means that the customer has modified their identity resolution ruleset to include more match rules or more match criteria that can identify more profiles as belonging to the same individual. For example, if a customer adds a match rule that matches profiles based on email address and phone number, instead of just email address, the ruleset will be able to match more profiles that have the same email address and phone number, resulting in a higher consolidation rate.

  References: Identity Resolution Calculated Insight: Consolidation Rates for Unified Profiles, Configure Identity Resolution Rulesets

• Question 62:

  Which data stream category should be assigned to use the data for time-based operations in segmentation and calculated insights?

  A. Individual

  B. Transaction

  C. Sales Order

  D. Engagement

  Correct Answer: B

  Data streams are the sources of data that are ingested into Data Cloud and mapped to the data model. Data streams have different categories that determine how the data is processed and used in Data Cloud. Transaction data streams are used for time-based operations in segmentation and calculated insights, such as filtering by date range, aggregating by time period, or calculating time-to-event metrics. Transaction data streams are typically used for event data, such as purchases, clicks, or visits, that have a timestamp and a value associated with them. References: Data Streams, Data Stream Categories

• Question 63:

  A customer has a custom Customer Email c object related to the standard Contact object in Salesforce CRM.

  This custom object stores the email address a Contact that they want to use for activation.

  To which data entity is mapped?

  A. Contact

  B. Contact Point_Email

  C. Custom customer Email__c object

  D. Individual

  Correct Answer: B

  The Contact Point_Email object is the data entity that represents an email address associated with an individual in Data Cloud. It is part of the Customer 360 Data Model, which is a standardized data model that defines common entities and

  relationships for customer data. The Contact Point_Email object can be mapped to any custom or standard object that stores email addresses in Salesforce CRM, such as the custom Customer Email__c object. The other options are not the

  correct data entities to map to because:

  The Contact object is the data entity that represents a person who is associated with an account that is a customer, partner, or competitor in Salesforce CRM. It is not the data entity that represents an email address in Data Cloud.

  The custom Customer Email__c object is not a data entity in Data Cloud, but a custom object in Salesforce CRM. It can be mapped to a data entity in Data Cloud, such as the Contact Point_Email object, but it is not a data entity itself.

  The Individual object is the data entity that represents a unique person in Data Cloud. It is the core entity for managing consent and privacy preferences, and it can be related to one or more contact points, such as email addresses, phone

  numbers, or social media handles. It is not the data entity that represents an email address in Data Cloud. References: Customer 360 Data Model: Individual and Contact Points - Salesforce, Contact Point_Email | Object Reference for the

  Salesforce Platform | Salesforce Developers, [Contact | Object Reference for the Salesforce Platform | Salesforce Developers], [Individual | Object Reference for the Salesforce Platform | Salesforce Developers]

• Question 64:

  Northern Trail Outfitters (NTO) wants to connect their B2C Commerce data with Data Cloud and bring two years of transactional history into Data Cloud.

  What should NTO use to achieve this?

  A. B2C Commerce Starter Bundles

  B. Direct Sales Order entity ingestion

  C. Direct Sales Product entity ingestion

  D. B2C Commerce Starter Bundles plus a custom extract

  Correct Answer: D

  The B2C Commerce Starter Bundles are predefined data streams that ingest order and product data from B2C Commerce into Data Cloud. However, the starter bundles only bring in the last 90 days of data by default. To bring in two years of transactional history, NTO needs to use a custom extract from B2C Commerce that includes the historical data and configure the data stream to use the custom extract as the source. The other options are not sufficient to achieve this because: B2C Commerce Starter Bundles only ingest the last 90 days of data by default. Direct Sales Order entity ingestion is not a supported method for connecting B2C Commerce data with Data Cloud. Data Cloud does not provide a direct-access connection for B2C Commerce data, only data ingestion. Direct Sales Product entity ingestion is not a supported method for connecting B2C Commerce data with Data Cloud. Data Cloud does not provide a direct-access connection for B2C Commerce data, only data ingestion. References: Create a B2C Commerce Data Bundle - Salesforce, B2C Commerce Connector - Salesforce, Salesforce B2C Commerce Pricing Plans and Costs

• Question 65:

  Cumulus Financial created a segment called High Investment Balance Customers. This is a foundational segment that includes several segmentation criteria the marketing team should consistently use.

  Which feature should the consultant suggest the marketing team use to ensure this consistency when creating future, more refined segments?

  A. Create new segments using nested segments.

  B. Create a High Investment Balance calculated insight.

  C. Package High Investment Balance Customers in a data kit.

  D. Create new segments by cloning High Investment Balance Customers.

  Correct Answer: A

  Nested segments are segments that include or exclude one or more existing segments. They allow the marketing team to reuse filters and maintain consistency in their data by using an existing segment to build a new one. For example, the marketing team can create a nested segment that includes High Investment Balance Customers and excludes customers who have opted out of email marketing. This way, they can leverage the foundational segment and apply additional criteria without duplicating the rules. The other options are not the best features to ensure consistency because: A calculated insight is a data object that performs calculations on data lake objects or CRM data and returns a result. It is not a segment and cannot be used for activation or personalization. A data kit is a bundle of packageable metadata that can be exported and imported across Data Cloud orgs. It is not a feature for creating segments, but rather for sharing components. Cloning a segment creates a copy of the segment with the same rules and filters. It does not allow the marketing team to add or remove criteria from the original segment, and it may create confusion and redundancy. References: Create a Nested Segment - Salesforce, Save Time with Nested Segments (Generally Available) - Salesforce, Calculated Insights - Salesforce, Create and Publish a Data Kit Unit | Salesforce Trailhead, Create a Segment in Data Cloud - Salesforce

• Question 66:

  What does it mean to build a trust-based, first-party data asset?

  A. To provide transparency and security for data gathered from individuals who provide consent for its use and receive value in exchange

  B. To provide trusted, first-party data in the Data Cloud Marketplace that follows all compliance regulations

  C. To ensure opt-in consents are collected for all email marketing as required by law

  D. To obtain competitive data from reliable sources through interviews, surveys, and polls

  Correct Answer: A

  Building a trust-based, first-party data asset means collecting, managing, and activating data from your own customers and prospects in a way that respects their privacy and preferences. It also means providing them with clear and honest information about how you use their data, what benefits they can expect from sharing their data, and how they can control their data. By doing so, you can create a mutually beneficial relationship with your customers, where they trust you to use their data responsibly and ethically, and you can deliver more relevant and personalized experiences to them. A trust-based, first-party data asset can help you improve customer loyalty, retention, and growth, as well as comply with data protection regulations and standards. References: Use first-party data for a powerful digital experience, Why first-party data is the key to data privacy, Build a first-party data strategy

• Question 67:

  A consultant has an activation that is set to publish every 12 hours, but has discovered that updates to the data prior to activation are delayed by up to 24 hours.

  Which two areas should a consultant review to troubleshoot this issue? Choose 2 answers

  A. Review data transformations to ensure they're run after calculated insights.

  B. Review calculated insights to make sure they're run before segments are refreshed.

  C. Review segments to ensure they're refreshed after the data is ingested.

  D. Review calculated insights to make sure they're run after the segments are refreshed.

  Correct Answer: BC

  The correct answer is B and C because calculated insights and segments are both dependent on the data ingestion process. Calculated insights are derived from the data model objects and segments are subsets of data model objects that meet certain criteria. Therefore, both of them need to be updated after the data is ingested to reflect the latest changes. Data transformations are optional steps that can be applied to the data streams before they are mapped to the data model objects, so they are not relevant to the issue. Reviewing calculated insights to make sure they're run after the segments are refreshed (option D) is also incorrect because calculated insights are independent of segments and do not need to be refreshed after them. References: Salesforce Data Cloud Consultant uide, Data Ingestion and Modeling, Calculated Insights, Segments

• Question 68:

  Which configuration supports separate Amazon S3 buckets for data ingestion and activation?

  A. Dedicated S3 data sources in Data Cloud setup

  B. Multiple S3 connectors in Data Cloud setup

  C. Dedicated S3 data sources in activation setup

  D. Separate user credentials for data stream and activation target

  Correct Answer: A

  To support separate Amazon S3 buckets for data ingestion and activation, you need to configure dedicated S3 data sources in Data Cloud setup. Data sources are used to identify the origin and type of the data that you ingest into Data Cloud1. You can create different data sources for each S3 bucket that you want to use for ingestion or activation, and specify the bucket name, region, and access credentials. This way, you can separate and organize your data by different criteria, such as brand, region, product, or business unit3. The other options are incorrect because they do not support separate S3 buckets for data ingestion and activation. Multiple S3 connectors are not a valid configuration in Data Cloud setup, as there is only one S3 connector available4. Dedicated S3 data sources in activation setup are not a valid configuration either, as activation setup does not require data sources, but activation targets5. Separate user credentials for data stream and activation target are not sufficient to support separate S3 buckets, as you also need to specify the bucket name and region for each data source2. References: Data Sources Overview, Amazon S3 Storage Connector, Data Spaces Overview, Data Streams Overview, Data Activation Overview

• Question 69:

  What is Data Cloud's primary value to customers?

  A. To provide a unified view of a customer and their related data

  B. To connect all systems with a golden record

  C. To create a single source of truth for all anonymous data

  D. To create personalized campaigns by listening, understanding, and acting on customer behavior

  Correct Answer: A

  Data Cloud is a platform that enables you to activate all your customer data across Salesforce applications and other systems. Data Cloud allows you to create a unified profile of each customer by ingesting, transforming, and linking data from various sources, such as CRM, marketing, commerce, service, and external data providers. Data Cloud also provides insights and analytics on customer behavior, preferences, and needs, as well as tools to segment, target, and personalize customer interactions. Data Cloud's primary value to customers is to provide a unified view of a customer and their related data, which can help you deliver better customer experiences, increase loyalty, and drive growth. References: Salesforce Data Cloud, When Data Creates Competitive Advantage

• Question 70:

  Which consideration related to the way Data Cloud ingests CRM data is true?

  A. CRM data cannot be manually refreshed and must wait for the next scheduled synchronization,

  B. The CRM Connector's synchronization times can be customized to up to 15-minute intervals.

  C. Formula fields are refreshed at regular sync intervals and are updated at the next full refresh.

  D. The CRM Connector allows standard fields to stream into Data Cloud in real time.

  Correct Answer: D

  The correct answer is D. The CRM Connector allows standard fields to stream into Data Cloud in real time. This means that any changes to the standard fields in the CRM data source are reflected in Data Cloud almost instantly, without

  waiting for the next scheduled synchronization. This feature enables Data Cloud to have the most up-to-date and accurate CRM data for segmentation and activation.

  The other options are incorrect for the following reasons:

  CRM data can be manually refreshed at any time by clicking the Refresh button on the data stream detail page2. This option is false.

  The CRM Connector's synchronization times can be customized to up to 60-minute intervals, not 15-minute intervals3. This option is false.

  Formula fields are not refreshed at regular sync intervals, but only at the next full refresh4. A full refresh is a complete data ingestion process that occurs once every 24 hours or when manually triggered.

  This option is false.

  References:

  1.

  Connect and Ingest Data in Data Cloud article on Salesforce Help

  2.

  Data Sources in Data Cloud unit on Trailhead

  3.

  Data Cloud for Admins module on Trailhead

  4.

  [Formula Fields in Data Cloud] unit on Trailhead

  5.

  [Data Streams in Data Cloud] unit on Trailhead