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These two ways can help Data Cloud honor a request to be forgotten by a customer. The Consent API allows you to set a consent flag for an individual that prevents further processing of their data and deletes their records from source data streams. The delete from file functionality allows you to upload a file with individual IDs that will be deleted from Data Cloud. References: https://help.salesforce.com/s/articleView?id=sf.c360_a_data_cloud_consent_api.htm &type=5https://help.salesforce.com/s/articleView?id=sf.c360_a_data_cloud_delete_from_file.htm &type=5

To create a multi-dimensional metric to identify unified individual lifetime value (LTV), the administrator needs to join the following data model objects (DMOs) in the Calculated Insight:

Unified Individual: This DMOrepresents the unified profile of an individual, which contains attributes from multiple sources.

Unified Link Individual: This DMO represents the link between an Individual DMO and a Unified Individual DMO.

Sales Order: This DMO represents a transaction or purchase made by an individual.

The sequence of joins should start from the Unified Individual DMO, then join the Unified Link Individual DMO using the UnifiedIndividualId field, and then join the Sales Order DMO usingthe IndividualId field. This way, the administrator can access the sales order data for each unified individual and calculate their lifetime value.

These two features are impacted by the timezone setting in the org Data Cloud is provisioned in. The segment schedule determines how often a segment is refreshed based on the selected timezone. The activation schedule determines how often a segment is exported to an activation target based on the selected timezone. References:https://help.salesforce.com/s/articleView?id=sf.c360_a_segmentation_schedule.htm &type=5https://help.salesforce.com/s/articleView?id=sf.c360_a_activatio n_schedule.htm&type=5

QUESTIONNO: 38

Which three out-of-the-box connectors are available for Data Cloud?

A. Marketing Cloud

B. B2C Commerce

C. Slack Connector

D. Amazon S3

E. Amazon Redshift Connector

Answer: A, B, D

These three out-of-the-box connectors are available for Data Cloud. They allow you to ingest data from Marketing Cloud, B2C Commerce, or Amazon S3 into Data Cloud and map it to the Data Cloud data model. References:https://help.sa lesforce.com/s/articleView?id=sf.c360_a_connectors.htm&type=5

The Ignore Empty Value option is a setting for reconciliation rules, which determine the logic for data selection in a unified profile7. If this option is enabled, empty fields are ignored when applying the reconciliation rule. For example, if the rule is to select the most frequent value, and one of the values is empty, it will not be counted as a frequency.

COALESCE is the function that returns the first value from a list that isn’t empty. It takes a list of values asarguments and returns the first non-empty value. For example, COALESCE(NULL, ‘’, ‘Hello’, ‘World’) returns ‘Hello’. If all values are empty, it returns NULL. References: COALESCE

These are the three data categories to select from when setting up the data source object or schema for data ingestion. Engagement data includes information about howcustomers interact with a brand or product, such as clicks, views, likes, etc. Order data includes information about transactions or purchases made by customers, such as order ID, amount, date, etc. Profile data includes information about customers’ attributes or preferences, such as name, email, gender, etc. References: [Data Categories]

Dimensions are attributes that can be used to group or filter data in calculated insights. You can include dimensions as attribute data in an activation by selecting them from the available attributes list.References:https://help.salesforce.com/s/articleView?id=sf.c360_a_data_cloud_calculated_insights.htm &type=5

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

 The reason for the activated count being smaller than the segment count is A. Data Cloud enforces the presence of Contact Point for Marketing Cloud activations. If the individual does not have a related Contact Point, it will not be activated. A Contact Point is a data model object that represents a channel or method of communication with an individual, such as email, phone, or social media. For Marketing Cloud activations, Data Cloud requires that the individual has a related Contact Point of type Email, which contains a valid email address. If the individual does not have such a Contact Point, or if the Contact Point is missing or invalid, the individual will not be activated and will not receive the email communication. Therefore, the activated count may be lower than the segment count, depending on how many individuals in the segment have a valid email Contact Point. References: Salesforce Data Cloud Consultant Exam Guide, Contact Point, Marketing Cloud Activation

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 use cases that are considered a good fit for Data Cloud are:

To ingest and unify data from various sources to reconcile customer identity. Data Cloud can help customers bring all their data, whether streaming or batch, into Salesforce and map it to a common data model. Data Cloud can also help customers resolve identities across different channels and sources and create unified profiles of their customers.

To use harmonized data to more accurately understand the customer and business impact. Data Cloud can help customers transform and cleanse their data before using it, and enrich it with calculated insights and related attributes. Data Cloud can also help customers create segments and audiences based on their data and activate them in any channel. Data Cloud can also help customers use AI to predict customer behavior and outcomes.

The other two options are not use cases that are considered a good fit for Data Cloud. Data Cloud does not provide features to create and orchestrate cross-channel marketing messages, as this is typically handled by other Salesforce solutions such as Marketing Cloud. Data Cloud also does not eliminate the need for separate business intelligence and IT data management tools, as it is designed to work with them and complement their capabilities.

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