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Salesforce Marketing-Cloud-Intelligence Exam Syllabus Topics:
Topic
Details
Topic 1
- Harmonization Center (Patterns
- Data Classification
- Validation): Salesforce marketing professionals will learn about the Harmonization Center’s capabilities, including classification rules, validation lists, patterns, and harmonized dimensions to ensure data reliability.
Topic 2
- Overarching Entities: Salesforce marketing professionals will deepen their understanding of overarching entities, their use cases, and application, crucial for strategic data organization and analysis.
Topic 3
- Harmonization Best Practices: Salesforce marketing professionals will analyze harmonization methods, properties, and their advantages and disadvantages, enhancing skills for optimizing data consistency across platforms.
Topic 4
- Data Integration Code Ability: This section evaluates proficiency with common Marketing Cloud Intelligence functions, enabling Salesforce marketing professionals to integrate diverse data sources effectively for comprehensive marketing intelligence.
Topic 5
- Calculated Dimensions & Measurements: This section measures skills in using calculated objects, recognizing aggregation types, and employing these tools for tailored marketing analytics.
Topic 6
- Data Update Permissions: This area tests knowledge of permissions and settings related to data updates. It includes understanding parent-child setups and managing the "Source of Truth" for data accuracy.
Topic 7
- Mapping: Marketing professionals will focus on Marketing Cloud Intelligence ingestion capabilities, assessing knowledge of data mapping processes and outcomes critical to efficient data organization.
Topic 8
- QA Ability: This section focuses on common QA steps for various scenarios, enabling Salesforce marketing professionals to ensure data quality and platform performance.
Topic 9
- Data Model: In this domain, marketing professionals will explore data model entities, their relationships, and attributes within Marketing Cloud Intelligence.
Topic 10
- Design Feasibility: This area evaluates the ability to identify valid and invalid solutions from solution design diagrams, ensuring effective and scalable platform designs.
Topic 11
- Vlookup: This section evaluates proficiency of marketing professionals in Vlookup statements and their properties, ensuring accurate data referencing and streamlined data manipulation for marketing intelligence tasks.
Topic 12
- Data Fusion: This topic focuses on the use cases and properties of Data Fusion, equipping marketing professionals to merge datasets effectively for comprehensive marketing insights.
Salesforce Marketing Cloud Intelligence Accredited Professional Exam Sample Questions (Q59-Q64):
NEW QUESTION # 59
Your client is interested in ingesting the below file:
The client decided to upload the file to a new generic data stream type and map 'Date' to 'Day' and 'Number of Topics' to a generic custom metric.
In regards to the fields 'Meeting Code' and 'Meeting Name', your client is debating several options.
Which two options would you recommend in order to avoid data loss?
- A. Concatenation of both 'Meeting Code' and 'Meeting Name' will be mapped to 'Main Generic Entity Key'.
'Meeting Code' will be mapped to 'Main Generic Entity Attribute 1'.
'Meeting Name' will be mapped to 'Main Generic Entity Attribute 2'. - B. 'Meeting Code' will be mapped to 'Main Generic Entity Attribute 1'.
'Meeting Name' will be mapped to 'Main Generic Entity Attribute 2'. - C. 'Meeting Code' will be mapped to 'Main Generic Entity Key'.
'Meeting Name' will be mapped to 'Main Generic Entity custom attribute'. - D. 'Meeting Code' will be mapped to 'Main Generic Entity Key'.
'Meeting Name' will be mapped to 'Generic Entity 2 Key'. - E. 'Meeting Code' will be mapped to 'Main Generic Entity custom attribute'.
'Meeting Name' will be mapped to 'Generic Entity Key'
Answer: A,C
Explanation:
To avoid data loss and ensure each meeting is uniquely identified and its details are preserved, two mappings are recommended:
Option A:
* 'Meeting Code' should be mapped to the 'Main Generic Entity Key' to uniquely identify each meeting.
* 'Meeting Name' should be mapped to a 'Main Generic Entity custom attribute' to store additional information about the meeting.
Option E:
* Concatenation of 'Meeting Code' and 'Meeting Name' should be mapped to 'Main Generic Entity Key'.
This ensures a unique identifier for each meeting is created combining both pieces of information, preventing any mix-ups between meetings with similar codes or names.
* Additionally, mapping 'Meeting Code' and 'Meeting Name' to their respective 'Main Generic Entity Attribute' fields will allow for more detailed filtering and reporting capabilities within Marketing Cloud Intelligence.
NEW QUESTION # 60
Your client is interested in ingesting the below file:
The client decided to upload the file to a new generic data stream type and map 'Date' to 'Day' and 'Number of Topics' to a generic custom metric.
In regards to the fields 'Meeting Code' and 'Meeting Name', your client is debating several options.
Which two options would you recommend in order to avoid data loss?
- A. Concatenation of both 'Meeting Code' and 'Meeting Name' will be mapped to 'Main Generic Entity Key'.
'Meeting Code' will be mapped to 'Main Generic Entity Attribute 1'. - B. 'Meeting Code' will be mapped to 'Main Generic Entity Attribute 1'.
'Meeting Name' will be mapped to 'Main Generic Entity Attribute 2'. - C. 'Meeting Code' will be mapped to 'Main Generic Entity Key'.
'Meeting Name' will be mapped to 'Main Generic Entity custom attribute'. - D. 'Meeting Code' will be mapped to 'Main Generic Entity Key'.
'Meeting Name' will be mapped to 'Generic Entity 2 Key'. - E. 'Meeting Code' will be mapped to 'Main Generic Entity custom attribute'.
'Meeting Name' will be mapped to 'Generic Entity Key'
Answer: A,C
Explanation:
'Meeting Name' will be mapped to 'Main Generic Entity Attribute 2'.
Explanation:
To avoid data loss and ensure each meeting is uniquely identified and its details are preserved, two mappings are recommended:
Option A:
'Meeting Code' should be mapped to the 'Main Generic Entity Key' to uniquely identify each meeting.
'Meeting Name' should be mapped to a 'Main Generic Entity custom attribute' to store additional information about the meeting.
Option E:
Concatenation of 'Meeting Code' and 'Meeting Name' should be mapped to 'Main Generic Entity Key'. This ensures a unique identifier for each meeting is created combining both pieces of information, preventing any mix-ups between meetings with similar codes or names.
Additionally, mapping 'Meeting Code' and 'Meeting Name' to their respective 'Main Generic Entity Attribute' fields will allow for more detailed filtering and reporting capabilities within Marketing Cloud Intelligence.
NEW QUESTION # 61
An implementation engineer has been asked by a client for assistance with the following problem:
The below dataset was ingested:
However, when performing QA and querying a pivot table with Campaign Category and Clicks, the value for Type' is 4.
What could be the reason for this discrepancy?
- A. The measurement 'Clicks' is set as a percentage.
- B. A mapping formula was populated, indicating not to bring Type! values.
- C. The aggregation function is set as LIFETIME
- D. The aggregation function is set as AVG
Answer: D
Explanation:
The discrepancy of 'Clicks' being reported as 4 for 'Type1' when the sum of clicks in the dataset for 'Type1' is 8 (2 on 02/02/2021 and 6 on 03/02/2021) suggests that the aggregation function used in the pivot table is set to average (AVG) rather than sum. Salesforce Marketing Cloud Intelligence allows setting different aggregation functions for metrics, and setting it to average would result in such a discrepancy when more than one entry for the same type exists. Reference: Salesforce Marketing Cloud Intelligence documentation on custom measurements and data aggregations explains how to set and understand different aggregation functions.
NEW QUESTION # 62
Source 3:
Via the harmonization Center, the Client has created Patterns and applied a classification rule using source 2.
While performing QA, you have spotted that the final value of clicks for Product Group Ais 10, where it should've been i5.
How can an implementation engineer fix this discrepancy?
- A. Upload both source 1 and 3 to the same data stream type in order to be able to generate Patterns from them.
- B. Leave the "Case Sensitive" checkbox in the data classification unchecked
- C. Uncheck the "Case Sensitive" checkbox in the data classification
- D. Toggle the 'Structure Compliant' OFF.
Answer: C
Explanation:
Case Sensitivity Issue:
The discrepancy in the "Clicks" value for Product Group A (10 instead of 15) likely arises from a mismatch caused by case sensitivity in the classification rules. If some data entries use different capitalization (e.g., "Product Group A" vs. "product group a"), the system might treat them as distinct entries, leading to incorrect aggregations.
Solution:
By unchecking the "Case Sensitive" checkbox, the harmonization process will treat entries with different capitalization as the same value. This ensures consistent classification and resolves discrepancies in aggregated metrics like "Clicks."
NEW QUESTION # 63
An implementation engineer has been asked by a client for assistance with the following problem:
The below dataset was ingested:
However, when performing QA and querying a pivot table with Campaign Category and Clicks, the value for Type' is 4.
What could be the reason for this discrepancy?
- A. The measurement 'Clicks' is set as a percentage.
- B. A mapping formula was populated, indicating not to bring Type! values.
- C. The aggregation function is set as LIFETIME
- D. The aggregation function is set as AVG
Answer: D
Explanation:
The discrepancy of 'Clicks' being reported as 4 for 'Type1' when the sum of clicks in the dataset for 'Type1' is
8 (2 on 02/02/2021 and 6 on 03/02/2021) suggests that the aggregation function used in the pivot table is set to average (AVG) rather than sum. Salesforce Marketing Cloud Intelligence allows setting different aggregation functions for metrics, and setting it to average would result in such a discrepancy when more than one entry for the same type exists. References: Salesforce Marketing Cloud Intelligence documentation on custom measurements and data aggregations explains how to set and understand different aggregation functions.
NEW QUESTION # 64
......
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