Question 1

A consultant is setting up a data stream with transactional data, Which field type should the consultant choose to ensure that leading zeros in the purchase order
number are preserved?

Accepted Answer

The field type Text should be chosen to ensure that leading zeros in the purchase order number are preserved. This is because text fields store alphanumeric
characters as strings, and do not remove any leading or trailing characters. On the other hand, number, decimal, and serial fields store numeric values as
numbers, and automatically remove any leading zeros when displaying or exporting the data123. Therefore, text fields are more suitable for storing data that needs
to retain its original format, such as purchase order numbers, zip codes, phone numbers, etc. References:
? Zeros at the start of a field appear to be omitted in Data Exports
? Keep First ‘0’ When Importing a CSV File
? Import and export address fields that begin with a zero or contain a plus symbol

Question 2

Cloud Kicks received a Request to be Forgotten by a customer.
In which two ways should a consultant use Data Cloud to honor this request? Choose 2 answers

Accepted Answer

To honor a Request to be Forgotten by a customer, a consultant should use Data Cloud in two ways:
? Add the Individual ID to a headerless file and use the delete from file functionality. This option allows the consultant to delete multiple Individuals from Data Cloud
by uploading a CSV file with their IDs1. The deletion process is asynchronous and can take up to 24 hours to complete1.
? Use the Consent API to suppress processing and delete the Individual and related records from source data streams. This option allows the consultant to submit
a Data Deletion request for an Individual profile in Data Cloud using the Consent API2. A Data Deletion request deletes the specified Individual entity and any
entities where a relationship has been defined between that entity’s identifying attribute and the Individual ID attribute2. The deletion process is reprocessed at 30,
60, and 90 days to ensure a full deletion2. The other options are not correct because:
? Deleting the data from the incoming data stream and performing a full refresh will not delete the existing data in Data Cloud, only the new data from the source
system3.
? Using Data Explorer to locate and manually remove the Individual will not delete the related records from the source data streams, only the Individual entity in
Data Cloud. References:
? Delete Individuals from Data Cloud
? Requesting Data Deletion or Right to Be Forgotten
? Data Refresh for Data Cloud
? [Data Explorer]

Question 3

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?

Accepted Answer

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

Question 4

Cumulus Financial wants to segregate Salesforce CRM Account data based on Country for its Data Cloud users.
What should the consultant do to accomplish this?

Accepted Answer

Data spaces are a feature that allows Data Cloud users to create subsets of data based on filters and permissions. Data spaces can be used to segregate data
based on different criteria, such as geography, business unit, or product line. In this case, the consultant can use the data spaces feature and apply filtering on the
Account data lake object based on Country. This way, the Data Cloud users can access only the Account data that belongs to their respective countries.
References: Data Spaces, Create a Data Space

Question 5

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

Accepted Answer

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 Exam
Guide, Data Ingestion and Modeling, Calculated Insights, Segments

Question 6

Northern Trail Outfitters uses B2C Commerce and is exploring implementing Data Cloud to get a unified view of its customers and all their order transactions.
What should the consultant keep in mind with regard to historical data ingesting order data using the B2C Commerce Order Bundle?

Accepted Answer

The B2C Commerce Order Bundle is a data bundle that creates a data stream to flow order data from a B2C Commerce instance to Data Cloud. However, this
data bundle does not ingest any historical data and only ingests new orders from the time the data stream is created. Therefore, if a consultant wants to ingest
historical order data, they need to use a different method, such as exporting the data from B2C Commerce and importing it to Data Cloud using a CSV file12.
References:
? Create a B2C Commerce Data Bundle
? Data Access and Export for B2C Commerce and Commerce Marketplace

Question 7

A consultant is integrating an Amazon 53 activated campaign with the customer's destination system.
In order for the destination system to find the metadata about the segment, which file on the 53 will
contain this information for processing?

Accepted Answer

The file on the Amazon S3 that will contain the metadata about the segment for processing is B. The json file. The json file is a metadata file that is generated
along with the csv file when a segment is activated to Amazon S3. The json file contains information such as the segment name, the segment ID, the segment
size, the segment attributes, the segment filters, and the segment schedule. The destination system can use this file to identify the segment and its properties, and
to match the segment data with the corresponding fields in the destination system. References: Salesforce Data Cloud Consultant Exam Guide, Amazon S3
Activation

Question 8

To import campaign members into a campaign in Salesforce CRM, a user wants to export the segment to Amazon S3. The resulting file needs to include the
Salesforce CRM Campaign ID in the name.
What are two ways to achieve this outcome? Choose 2 answers

Accepted Answer

The two ways to achieve this outcome are A and C. Include campaign identifier in the activation name and include campaign identifier in the filename
specification. These two options allow the user to specify the Salesforce CRM Campaign ID in the name of the file that is exported to Amazon S3. The activation
name and the filename specification are both configurable settings in the activation wizard, where the user can enter the campaign identifier as a text or a variable.
The activation name is used as the prefix of the filename, and the filename specification is used as the suffix of the filename. For example, if the activation name is
“Campaign_123” and the filename specification is “{segmentName}_{date}”, the resulting file name will be “Campaign_123_SegmentA_2023-12-18.csv”. This
way, the user can easily identify the file that corresponds to the campaign and import it into Salesforce CRM.
The other options are not correct. Option B is incorrect because hard coding the campaign identifier as a new attribute in the campaign activation is not possible.
The campaign activation does not have any attributes, only settings. Option D is incorrect because including the campaign identifier in the segment name is not
sufficient. The segment name is not used in the filename of the exported file, unless it is specified in the filename specification. Therefore, the user will not be able
to see the campaign identifier in the file name.

Question 9

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

Accepted Answer

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 activation1.
The other options are incorrect for the following reasons:
? A. CRM data can be manually refreshed at any time by clicking the Refresh button on the data stream detail page2. This option is false.
? B. The CRM Connector’s synchronization times can be customized to up to 60- minute intervals, not 15-minute intervals3. This option is false.
? C. 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
? : [Data Streams in Data Cloud] unit on Trailhead

Question 10

Which information is provided in a .csv file when activating to Amazon S3?

Accepted Answer

When activating to Amazon S3, the information that is provided in a .csv file is the activated data payload. The activated data payload is the data that is sent from
Data Cloud to the activation target, which in this case is an Amazon S3 bucket1. The activated data payload contains the attributes and values of the individuals or
entities that are included in the segment that is being activated2. The activated data payload can be used for various purposes, such as marketing, sales, service,
or analytics3. The other options are incorrect because they are not provided in a .csv file when activating to Amazon S3. Option A is incorrect because an audit log
is not provided in a .csv file, but it can be viewed in the Data Cloud UI under the Activation History tab4. Option C is incorrect because the metadata regarding the
segment definition is not provided in a .csv file, but it can be viewed in the Data Cloud UI under the Segmentation tab5. Option D is incorrect because the manifest
of origin sources within Data Cloud is not provided in a .csv file, but it can be viewed in the Data Cloud UI under the Data Sources tab. References: Data Activation
Overview, Create and Activate Segments in Data Cloud, Data Activation Use Cases, View Activation History, Segmentation Overview, [Data Sources Overview]