Question # 1
| Northern Trail Outfitters is using the Marketing Cloud Starter Data Bundles to bring Marketing Cloud data into Data Cloud.
What are two of the available datasets in Marketing Cloud Starter Data Bundles? Choose 2 answers | | A. Personalization | | B. MobileConnect | | C. Loyalty Management | | D. MobilePush |
B. MobileConnect
D. MobilePush
Explanation: The Marketing Cloud Starter Data Bundles are predefined data bundles that allow you to easily ingest data from Marketing Cloud into Data Cloud1. The available datasets in Marketing Cloud Starter Data Bundles are Email, MobileConnect, and MobilePush2. These datasets contain engagement events and metrics from different Marketing Cloud channels, such as email, SMS, and push notifications2. By using these datasets, you can enrich your Data Cloud data model with Marketing Cloud data and create segments and activations based on your marketing campaigns and journeys1. The other options are incorrect because they are not available datasets in Marketing Cloud Starter Data Bundles. Option A is incorrect because Personalization is not a dataset, but a feature of Marketing Cloud that allows you to tailor your content and messages to your audience3. Option C is incorrect because Loyalty Management is not a dataset, but a product of Marketing Cloud that allows you to create and manage loyalty programs for your customers4. References: Marketing Cloud Starter Data Bundles in Data Cloud, Connect Your Data Sources, Personalization in Marketing Cloud, Loyalty Management in Marketing Cloud
Question # 2
| When creating a segment on an individual, what is the result of using two separate containers linked by an AND as shown below?
GoodsProduct | Count | At Least | 1 Color | Is Equal To | red
AND
GoodsProduct | Count | At Least | 1 PrimaryProductCategory | Is Equal To | shoes | | A. Individuals who purchased at least one of any red’ product and also purchased at least one pair of ‘shoes’ | | B. Individuals who purchased at least one 'red shoes' as a single line item in a purchase | | C. Individuals who made a purchase of at least one 'red shoes’ and nothing else | | D. Individuals who purchased at least one of any 'red' product or purchased at least one pair of 'shoes' |
A. Individuals who purchased at least one of any red’ product and also purchased at least one pair of ‘shoes’
Explanation: When creating a segment on an individual, using two separate containers linked by an AND means that the individual must satisfy both the conditions in the containers. In this case, the individual must have purchased at least one product with the color attribute equal to ‘red’ and at least one product with the primary product category attribute equal to ‘shoes’. The products do not have to be the same or purchased in the same transaction. Therefore, the correct answer is A.
The other options are incorrect because they imply different logical operators or conditions. Option B implies that the individual must have purchased a single product that has both the color attribute equal to ‘red’ and the primary product category attribute equal to ‘shoes’.
Option C implies that the individual must have purchased only one product that has both the color attribute equal to ‘red’ and the primary product category attribute equal to ‘shoes’ and no other products. Option D implies that the individual must have purchased either one product with the color attribute equal to ‘red’ or one product with the primary product category attribute equal to ‘shoes’ or both, which is equivalent to using an OR operator instead of an AND operator. References:
Create a Container for Segmentation Create a Segment in Data Cloud Navigate Data Cloud Segmentation
Question # 3
| A client wants to bring in loyalty data from a custom object in Salesforce CRM that contains a point balance for accrued hotel points and airline points within the same record. The client wants to split these point systems into two separate records for better tracking and processing. What should a consultant recommend in this scenario? | | A. Clone the data source object. | | B. Use batch transforms to create a second data lake object. | | C. Create a junction object in Salesforce CRM and modify the ingestion strategy. | | D. Create a data kit from the data lake object and deploy it to the same Data Cloud org. |
B. Use batch transforms to create a second data lake object.
Explanation:
Batch transforms are a feature that allows creating new data lake objects based on existing data lake objects and applying transformations on them. This can be useful for splitting, merging, or reshaping data to fit the data model or business requirements. In this case, the consultant can use batch transforms to create a second data lake object that contains only the airline points from the original loyalty data object. The original object can be modified to contain only the hotel points. This way, the client can have two separate records for each point system and track and process them accordingly.
Question # 4
| 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. |
D. The CRM Connector allows standard fields to stream into Data Cloud in real time.
Question # 5
| 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 |
A. To provide transparency and security for data gathered from individuals who provide consent for its use and receive value in exchange
Explanation: 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 # 6
| Cumulus Financial is experiencing delays in publishing multiple segments simultaneously.
The company wants to avoid reducing the
frequency at which segments are published, while retaining the same segments in place
today.
Which action should a consultant take to alleviate this issue? | | A. Enable rapid segment publishing to all to segment to reduce generation time. | | B. Reduce the number of segments being published | | C. Increase the Data Cloud segmentation concurrency limit. | | D. Adjust the publish schedule start time of each segment to prevent overlapping
processes. |
D. Adjust the publish schedule start time of each segment to prevent overlapping
processes.
Question # 7
| A Data Cloud consultant recently added a new data source and mapped some of the data to a new custom data model object (DMO) that they want to use for creating segments. However, they cannot view the newly created DMO when trying to create a new segment.
What is the cause of this issue? | | A. Data has not yes been ingested into the DMO. | | B. The new DMO is not of category Profile. | | C. The new DMO does not have a relationship to the individual DMO | | D. Segmentation is only supported for the Individual and Unified Individual DMOs. |
B. The new DMO is not of category Profile.
Explanation: The cause of this issue is that the new custom data model object (DMO) is not of category Profile. A category is a property of a DMO that defines its purpose and functionality in Data Cloud. There are three categories of DMOs: Profile, Event, and Other. Profile DMOs are used to store attributes of individuals or entities, such as name, email, address, etc. Event DMOs are used to store actions or interactions of individuals or entities, such as purchases, clicks, visits, etc. Other DMOs are used to store any other type of data that does not fit into the Profile or Event categories, such as products, locations, categories, etc. Only Profile DMOs can be used for creating segments in Data Cloud, as segments are based on the attributes of individuals or entities. Therefore, if the new custom DMO is not of category Profile, it will not appear in the segmentation canvas. The other options are not correct because they are not the cause of this issue. Data ingestion is not a prerequisite for creating segments, as segments can be created based on the data model schema without actual data. The new DMO does not need to have a relationship to the individual DMO, as segments can be created based on any Profile DMO, regardless of its relationship to other DMOs. Segmentation is not only supported for the Individual and Unified Individual DMOs, as segments can be created based on any Profile DMO, including custom ones. References: Create a Custom Data Model Object from an Existing Data Model Object, Create a Segment in Data Cloud, Data Model Object Category
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