Pass Guaranteed Quiz Newest Marketing-Cloud-Intelligence - Marketing Cloud Intelligence Accredited Professional Exam Best Study Material
Pass Guaranteed Quiz Newest Marketing-Cloud-Intelligence - Marketing Cloud Intelligence Accredited Professional Exam Best Study Material
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Marketing-Cloud-Intelligence Best Study Material - Pass Guaranteed Marketing-Cloud-Intelligence - Marketing Cloud Intelligence Accredited Professional Exam First-grade Valid Test Guide
Many people choose to sign up for the Salesforce Marketing-Cloud-Intelligence certification examinations in order to advance their knowledge and abilities. We offer updated and actual Salesforce Marketing-Cloud-Intelligence Dumps questions that will be enough to get ready for the Salesforce Marketing-Cloud-Intelligence test. Our Salesforce Marketing-Cloud-Intelligence questions are 100% genuine and will certainly appear in the next Salesforce Marketing-Cloud-Intelligence test.
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Salesforce Marketing Cloud Intelligence Accredited Professional Exam Sample Questions (Q19-Q24):
NEW QUESTION # 19
What are two potential reasons for performance issues (when loading a dashboard) when using the CRM data stream type?
- A. No mappable measurements - all measurements are calculated
- B. When a data stream type ''CRM - Leads' is created, another complementary 'CRM - Opportunity' is created automatically.
- C. Pacing - daily rows are being created for every lead and opportunity keys
- D. The data is stored at the workspace level.
Answer: A,C
Explanation:
For performance issues when loading a dashboard using CRM data stream type:
* Pacing can create performance issues because daily rows for every lead and opportunity key can result in a very large number of rows, increasing load times.
* Having only calculated measurements means there are no direct, mappable values to query against, which can increase the computational load and affect performance.
NEW QUESTION # 20
A client wants to integrate their data within Marketing Cloud Intelligence to optimize their marketing Insights and cross-channel marketing activity analysis. Below are details regarding the different data sources and the number of data streams required for each source.
Which three advantages does a client gain from using Calculated Dimensions as the harmonization method for creating the Objective field?
- A. Ease of Maintenance - thelogic is written and populated in one centralized place
- B. Performance (Performance when loading a dashboard page) should be optimized as the values of calculated dimensions are stored within the database.
- C. Processing - creation of Calculated Dimensions will ease the processing time of the data streams it relates to
- D. Data model restrictions - Calculated Dimensions do not need to adhere to Marketing Cloud Intelligence's data model
- E. Scalability - future data streams that will follow similar logic will be automatically harmonized.
Answer: A,B,E
Explanation:
* Scalability: Using Calculated Dimensions allows the client to apply the same harmonization logic to future data streams, ensuring consistency and reducing the need for individual adjustments.
* Ease of Maintenance: With the logic centralized in Calculated Dimensions, any adjustments or updates are applied in one place, simplifying ongoing management.
* Performance: Calculated Dimensions can improve dashboard performance because their values are pre-computed and stored, reducing the need for real-time calculations when loading dashboards.
NEW QUESTION # 21
Which two statements are correct regarding LiteConnect?
- A. Data coming from LiteConnect cannot be harmonized with the rest of the workspace data via the harmonization center at a later step.
- B. It does not require any identification of entities, keys or any other categorization.
- C. The dataset does not conform to the standard data model
- D. All of the dimensions mapped within a LiteConnect data stream are considered overarching entities.
Answer: B,C
Explanation:
LiteConnect is a feature in Salesforce Marketing Cloud Intelligence that allows users to bring external data into the platform quickly and easily. Here are the correct statements regarding LiteConnect:
A . LiteConnect allows for a quick setup by not requiring detailed identification of entities, keys, or categorization. Users can upload files without having to conform to the standard data model, which speeds up the process of data integration.
B . With LiteConnect, datasets are uploaded in their native format and do not conform to the standard data model of Marketing Cloud Intelligence. This means that the original structure of the dataset is maintained, and there is no need for extensive transformation or mapping upon the initial data import.
For C and D: While LiteConnect datasets might not conform to the standard data model initially, there are capabilities within Marketing Cloud Intelligence to further categorize and harmonize this data if needed. Therefore, C is not entirely correct, and D is incorrect because harmonization can indeed occur at a later step.
NEW QUESTION # 22
An Implementation engineer is requested to create anew harmonization field 'Offer'and apply the following logic:
The implementation engineer to use the Harmonization Center. Which of the below actions can help implement the new dimension 'Offer?
- A. Two separate patterns (filtered by Linkedin or AdRoll sources).
Another single pattern for Campaign Name (filtered by Google Analytics source).
A total of 3 patterns. - B. Two separate patterns (filtered by Linkedln or AdRoll sources).Another single pattern for Web Analytics Site Source (filtered by Google Analytics source), extracting all three positions A total of 3 patterns.
- C. Two separate patterns (filtered by Linkedin or AdRoll sources)
Within Google Analytics' mapping: A formula that reflects the logic above will be populated within a Campaign custom attribute.
Another pattern to be created for the newly campaign attribute (filtered by Google Analytics source).
A total of 3 patterns - D. Two separate patterns (filtered by Linkedin or AdRoll sources)
Within Google Analytics' mapping A formula that reflects the logic above will be populated within a Web Analytics Site custom attribute Another pattern to be created for the newly Web Analytics Site custom attribute (filtered by Google Analytics source).
A total of 3 patterns.
Answer: C
Explanation:
To implement the new harmonization field 'Offer', the implementation engineer would create two separate harmonization patterns for LinkedIn and AdRoll sources, extracting the 'Campaign Name' using the specified delimiter and position. Then, within Google Analytics' mapping, a custom attribute for the 'Campaign' would be created to apply the formula logic based on the source. This allows for the harmonization of campaign data across different platforms, ensuring consistency in the reporting and analysis within Marketing Cloud Intelligence. The total patterns required would be three, one for each data source involved.
NEW QUESTION # 23
A client provides the following three files:
File A:
File B:
File C:
File A was uploaded using the Ads data stream type.
The client would like to create this view (data from Files B & C) in Datorama:
Which proposed solution would cause a false connection between the two files?
- A. VLOOKUP in Data Stream C. Vlookup will return "MB Name"
- B. Custom classification
- C. Data Classification
- D. VLOOKUP in Data Stream B. Vlookup will return "Day" and "Installs"
Answer: D
Explanation:
With File A uploaded using the Ads data stream type, the client wishes to create a view incorporating data from Files B & C.
A false connection would occur if VLOOKUP in Data Stream B is used incorrectly to return "Day" and "Installs". In this scenario, VLOOKUP might inaccurately link data based on MB Name between File B and File A or File C, which do not have a "Day" field to correctly join on. Moreover, "Installs" data in File B doesn't exist, so VLOOKUP cannot correctly return this information. The correct method would be to use the "Media Buy New Name" to link File B and File C since they both have this field, ensuring accurate connection and avoiding data mismatches or false connections.
NEW QUESTION # 24
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