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Salesforce Certified Data Cloud Consultant Sample Questions (Q19-Q24):

NEW QUESTION # 19
A customer has outlined requirements to trigger a journey for an abandoned browse behavior. Based on the requirements, the consultant determines they will use streaming insights to trigger a data action to Journey Builder every hour.
How should the consultant configure the solution to ensure the data action is triggered at the cadence required?

A. Configure the data to be ingested in hourly batches.

B. Set the activation schedule to hourly.

C. Set the insights aggregation time window to 1 hour.

D. Set the journey entry schedule to run every hour.

Answer: C

Explanation:
Explanation
Streaming insights are computed from real-time engagement events and can be used to trigger data actions based on pre-set rules. Data actions are workflows that send data from Data Cloud to other systems, such as Journey Builder. To ensure that the data action is triggered every hour, the consultant should set the insights aggregation time window to 1 hour. This means that the streaming insight will evaluate the events that occurred within the last hour and execute the data action if the conditions are met. The other options are not relevant for streaming insights and data actions. References: Streaming Insights and Data Actions Limits and Behaviors, Streaming Insights, Streaming Insights and Data Actions Use Cases, Use Insights in Data Cloud, 6 Ways the Latest Marketing Cloud Release Can Boost Your Campaigns

NEW QUESTION # 20
Which two requirements must be met for a calculated insight to appear in the segmentation canvas?
Choose 2 answers

A. The metrics of the calculated insights must only contain numeric values.

B. The primary key of the segmented table must be a dimension in the calculated insight.

C. The calculated insight must contain a dimension including the Individual or Unified Individual Id.

D. The primary key of the segmented table must be a metric in the calculated insight.

Answer: B,C

Explanation:
A calculated insight is a custom metric or measure that is derived from one or more data model objects or data lake objects in Data Cloud. A calculated insight can be used in segmentation to filter or group the data based on the calculated value. However, not all calculated insights can appear in the segmentation canvas. There are two requirements that must be met for a calculated insight to appear in the segmentation canvas:
The calculated insight must contain a dimension including the Individual or Unified Individual Id. A dimension is a field that can be used to categorize or group the data, such as name, gender, or location. The Individual or Unified Individual Id is a unique identifier for each individual profile in Data Cloud. The calculated insight must include this dimension to link the calculated value to the individual profile and to enable segmentation based on the individual profile attributes.
The primary key of the segmented table must be a dimension in the calculated insight. The primary key is a field that uniquely identifies each record in a table. The segmented table is the table that contains the data that is being segmented, such as the Customer or the Order table. The calculated insight must include the primary key of the segmented table as a dimension to ensure that the calculated value is associated with the correct record in the segmented table and to avoid duplication or inconsistency in the segmentation results.
Create a Calculated Insight, Use Insights in Data Cloud, Segmentation

NEW QUESTION # 21
Cumulus Financial uses Data Cloud to segment banking customers and activate them for direct mail via a Cloud File Storage activation. The company also wants to analyze individuals who have been in the segment within the last 2 years.
Which Data Cloud component allows for this?

A. Segment exclusion

B. Nested segments

C. Calculated insights

D. Segment membership data model object

Answer: D

Explanation:
Data Cloud allows customers to analyze the segment membership history of individuals using the Segment Membership data model object. This object stores information about when an individual joined or left a segment, and can be used to create reports and dashboards to track segment performance over time. Cumulus Financial can use this object to filter individuals who have been in the segment within the last 2 years and compare them with other metrics.
The other options are not Data Cloud components that allow for this analysis. Segment exclusion is a feature that allows customers to remove individuals from a segment based on another segment. Nested segments are segments that are created from other segments using logical operators. Calculated insights are derived attributes that are created from existing data using formulas.
References:
* Segment Membership Data Model Object
* Data Cloud Reports and Dashboards
* Create a Segment in Data Cloud

NEW QUESTION # 22
A consultant is setting up Data Cloud for a multi-brand organization and is using data spaces to segregate its data for various brands.
While starting the mapping of a data stream, the consultant notices that they cannot map the object for one of the brands.
What should the consultant do to make the object available for a new data space?

A. Navigate to the Data Space tab and select the object to be included in the new data space.

B. Create a batch transform to split data between different data spaces.

C. Copy data from the default data space to a new DMO using the Data Copy feature and link this DMO to the new data space.

D. Create a new data stream and map the second data stream to the data space.

Answer: A

NEW QUESTION # 23
Northern Trail Outfitters (NTO), an outdoor lifestyle clothing brand, recently started a new line of business. The new business specializes in gourmet camping food. For business reasons as well as security reasons, it's important to NTO to keep all Data Cloud data separated by brand.
Which capability best supports NTO's desire to separate its data by brand?

A. Data model objects for each brand

B. Data streams for each brand

C. Data spaces for each brand

D. Data sources for each brand

Answer: C

Explanation:
Data spaces are logical containers that allow you to separate and organize your data by different criteria, such as brand, region, product, or business unit1. Data spaces can help you manage data access, security, and governance, as well as enable cross-cloud data integration and activation2. For NTO, data spaces can support their desire to separate their data by brand, so that they can have different data models, rules, and insights for their outdoor lifestyle clothing and gourmet camping food businesses. Data spaces can also help NTO comply with any data privacy and security regulations that may apply to their different brands3. The other options are incorrect because they do not provide the same level of data separation and organization as data spaces. Data streams are used to ingest data from different sources into Data Cloud, but they do not separate the data by brand4. Data model objects are used to define the structure and attributes of the data, but they do not isolate the data by brand5. Data sources are used to identify the origin and type of the data, but they do not partition the data by brand. References: Data Spaces Overview, Create Data Spaces, Data Privacy and Security in Data Cloud, Data Streams Overview, Data Model Objects Overview, [Data Sources Overview]

NEW QUESTION # 24
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