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Free Data-Cloud-Consultant Exam Braindumps (page: 4)

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PDF with 170 Questions

A Data Cloud customer wants to adjust their identity resolution rules to increase their accuracy of matches. Rather than matching on email address, they want to review a rule that joins their CRM Contacts with their Marketing Contacts, where both use the CRM ID as their primary key.
Which two steps should the consultant take to address this new use case? Choose 2 answers

  1. Map the primary key from the two systems to Party Identification, using CRM ID as the identification name for both.
  2. Map the primary key from the two systems to party identification, using CRM ID as the identification name for individuals coming from the CRM, and Marketing ID as the identification name for individuals coming from the marketing platform.
  3. Create a custom matching rule for an exact match on the Individual ID attribute.
  4. Create a matching rule based on party identification that matches on CRM ID as the party identification name.

Answer(s): A,D

Explanation:

To address this new use case, the consultant should map the primary key from the two systems to Party Identification, using CRM ID as the identification name for both, and create a matching rule based on party identification that matches on CRM ID as the party identification name. This way, the consultant can ensure that the CRM Contacts and Marketing Contacts are matched based on their CRM ID, which is a unique identifier for each individual. By using Party Identification, the consultant can also leverage the benefits of this attribute, such as being able to match across different entities and sources, and being able to handle multiple values for the same individual. The other options are incorrect because they either do not use the CRM ID as the primary key, or they do not use Party Identification as the attribute type.


Reference:

Configure Identity Resolution Rulesets, Identity Resolution Match Rules, Data Cloud Identity Resolution Ruleset, Data Cloud Identity Resolution Config Input



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

  1. CRM data cannot be manually refreshed and must wait for the next scheduled synchronization,
  2. The CRM Connector's synchronization times can be customized to up to 15-minute intervals.
  3. Formula fields are refreshed at regular sync intervals and are updated at the next full refresh.
  4. The CRM Connector allows standard fields to stream into Data Cloud in real time.

Answer(s): D

Explanation:

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:
A . CRM data can be manually refreshed at any time by clicking the Refresh button on the data stream detail page. This option is false.
B . The CRM Connector's synchronization times can be customized to up to 60-minute intervals, not 15-minute intervals. This option is false.
C . Formula fields are not refreshed at regular sync intervals, but only at the next full refresh. A full refresh is a complete data ingestion process that occurs once every 24 hours or when manually triggered. This option is false.


Reference:

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



What does the Source Sequence reconciliation rule do in identity resolution?

  1. Includes data from sources where the data is most frequently occurring
  2. Identifies which individual records should be merged into a unified profile by setting a priority for specific data sources
  3. Identifies which data sources should be used in the process of reconcillation by prioritizing the most recently updated data source
  4. Sets the priority of specific data sources when building attributes in a unified profile, such as a first or last name

Answer(s): D

Explanation:

The Source Sequence reconciliation rule sets the priority of specific data sources when building attributes in a unified profile, such as a first or last name. This rule allows you to define which data source should be used as the primary source of truth for each attribute, and which data sources should be used as fallbacks in case the primary source is missing or invalid. For example, you can set the Source Sequence rule to use data from Salesforce CRM as the first priority, data from Marketing Cloud as the second priority, and data from Google Analytics as the third priority for the first name attribute. This way, the unified profile will use the first name value from Salesforce CRM if it exists, otherwise it will use the value from Marketing Cloud, and so on. This rule helps you to ensure the accuracy and consistency of the unified profile attributes across different data sources.


Reference:

Salesforce Data Cloud Consultant Exam Guide, Identity Resolution, Reconciliation Rules



Which two dependencies prevent a data stream from being deleted?

Choose 2 answers

  1. The underlying data lake object is used in activation.
  2. The underlying data lake object is used in a data transform.
  3. The underlying data lake object is mapped to a data model object.
  4. The underlying data lake object is used in segmentation.

Answer(s): B,C

Explanation:

To delete a data stream in Data Cloud, the underlying data lake object (DLO) must not have any dependencies or references to other objects or processes. The following two dependencies prevent a data stream from being deleted1:
Data transform: This is a process that transforms the ingested data into a standardized format and structure for the data model. A data transform can use one or more DLOs as input or output. If a DLO is used in a data transform, it cannot be deleted until the data transform is removed or modified. Data model object: This is an object that represents a type of entity or relationship in the data model. A data model object can be mapped to one or more DLOs to define its attributes and values. If a DLO is mapped to a data model object, it cannot be deleted until the mapping is removed or changed.


Reference:

1: Delete a Data Stream article on Salesforce Help
2: [Data Transforms in Data Cloud] unit on Trailhead
3: [Data Model in Data Cloud] unit on Trailhead






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