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Salesforce Marketing-Cloud-Intelligence Exam Syllabus Topics:
Topic
Details
Topic 1
- 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 2
- QA Ability: This section focuses on common QA steps for various scenarios, enabling Salesforce marketing professionals to ensure data quality and platform performance.
Topic 3
- 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 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
- 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 6
- CRM: This topic tests knowledge of CRM properties and their behavior within Marketing Cloud Intelligence. This knowledge is crucial for syncing customer relationship data with marketing campaigns.
Topic 7
- Data Model: In this domain, marketing professionals will explore data model entities, their relationships, and attributes within Marketing Cloud Intelligence.
Topic 8
- 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 9
- 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.
Topic 10
- Calculated Dimensions & Measurements: This section measures skills in using calculated objects, recognizing aggregation types, and employing these tools for tailored marketing analytics.
Topic 11
- 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.
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Salesforce Marketing Cloud Intelligence Accredited Professional Exam Sample Questions (Q53-Q58):
NEW QUESTION # 53
A technical architect is provided with the logic and Opportunity file shown below:
The opportunity status logic is as follows:
For the opportunity stages "Interest", "Confirmed Interest" and "Registered", the status should be "Open".
For the opportunity stage "Closed", the opportunity status should be closed Otherwise, return null for the opportunity status.
Given the above file and logic and assuming that the file is mapped in a generic data stream type with the following mapping
"Day" - Standard "Day" field
"Opportunity Key" > Main Generic Entity Key
"Opportunity Stage" + Generic Entity Key 2
A pivot table was created to present the count of opportunities in each stage. The pivot table is filtered on Jan 7th - 11th. Which option reflects the stage(s) the Opportunity key 123AA01 is associated with?
- A. Registered
- B. Interest
- C. Interest & Registered
- D. Confirmed Interest & Registered
- E. Confirmed Interest
Answer: C
Explanation:
Analyzing the Opportunity file with a filter set from January 7th to 11th, Opportunity Key '123AA01' appears under 'Interest' on January 6th and 8th, and under 'Registered' on January 10th. Therefore, during the specified date range, Opportunity Key '123AA01' is associated with both 'Interest' and 'Registered' stages. Salesforce Marketing Cloud Intelligence provides the capability to map and track opportunity stages over time, allowing for historical stage tracking and reporting. This answer aligns with the ability to use pivot tables to filter and display data by specific attributes and timeframes, as outlined in the Salesforce Marketing Cloud Intelligence documentation.
NEW QUESTION # 54
A client has integrated data from Facebook Ads, Twitter Ads, and Google Ads in Marketing Cloud Intelligence. For each data source, the data follows a naming convention as shown below:
Facebook Ads Naming Convention - Campaign Name:
Camp|D_CampName#Market_Objective#TargetAge_TargetGender
Twitter Ads Naming Convention - Media Buy Name:
Market|TargetAge|Objective|OrderID
' Google Ads Naming Convention - Media Buy Name:
Buying Type_Market_Objective
The client wants to harmonize their data on the common fields between these two platforms (i.e. Market and Objective) using the Harmonization 'Center.
In addition to the previous details, the client provides the following data sample:
Logic specification:
If a value is not present in the Validation List, return "Not Valid"
If a value is not present in the Classification File, return "Unclassified".
If the Harmonization center is used to harmonize the above data and files, what table will show the final output?
Answer: C
Explanation:
The correct table would be Option B.
The harmonization process would identify the 'Market' from the campaign or media buy name based on the delimiter and position rules specified in the naming conventions. The harmonized 'Market' would then be matched against the classification file and validation list. If a value does not match the validation list, it would return 'Not Valid', and if it's not present in the classification file, it would return 'Unclassified'. Option B is the only table showing the 'Not Valid' category which aligns with the logic specification provided.
NEW QUESTION # 55
What areunstable measurements?
- A. Measurements for which Aggregation Settings are set as 'Not Auto' and Granularity is set as 'Not Empty'.
- B. Measurements for which Aggregation Settings are set as 'Auto' and Granularity is set as 'None'.
- C. Measurements for which Aggregation Settings are set as 'Not Auto' and Granularity is set as 'None'.
- D. Measurements that are set with the LIFETIME aggregation function
Answer: C
Explanation:
Unstable measurements refer to metrics that are not aggregated in a standard manner across different grains of data, which can result in inconsistent or unpredictable results when reporting across different dimensions or time frames.
* Option C describes a scenario where measurements have manual (Not Auto) aggregation settings, meaning they do not automatically adjust to theaggregation level of the report. Combined with a Granularity setting of 'None', this can lead to instability because the metric isn't bound to a specific granularity, which can cause data inconsistencies or misinterpretations when analyzed at varying levels of detail.
NEW QUESTION # 56
Aclient has integrated the following files:
File A:
File B:
The client would like to link the two files in order to view the two KPIs ('Tasks Completed' and 'Tasks Assigned) alongside 'Employee Name' and/or
'Squad'.
The client set the following properties:
+ File Ais set as the Parent data stream
* Both files were uploaded to a generic data stream type.
* Override Media Buy Hierarchies is checked for file A.
* The 'Data Updates Permissions' set for file B is 'Update Attributes and Hierarchy'.
When filtering on the entire date range (1-30/8), and querying employee ID, Name and Squad with the two measurements - what will the result look like?
Answer: C
Explanation:
In Marketing Cloud Intelligence, when linking two data streams, the parent data stream (File A) provides the main structure. Since 'Override Media Buy Hierarchies' is checked for File A, the hierarchies from File B will be aligned with File A. Given 'Data UpdatesPermissions' set for file B as 'Update Attributes and Hierarchy', this means that attributes and hierarchy will be updated in the parent file based on the child file (File B), but the child file's metrics won't be associated with the parent file's date.
Hence, when filtering on the entire date range (1-30/8), the resulting view will align with the structure of the parent data stream, showing the KPIs ('Tasks Completed' from File A and 'Tasks Assigned' from File B) alongside the employee names and squads from the respective files. Since the employee IDs align, the data can be linked properly. However, since the dates do not align (File A data is from 01/08/2019 and File B from
15/08/2019), only attributes from File B will be updated without date association.
The result will look like Option C, where the employee names are corrected based on File B's data, the squads are added from File B, and the tasks_completed and tasks_assigned are displayed from their respective files.
The tasks_assigned from File B are shown without date association as File B's date doesn't match with File A's.
NEW QUESTION # 57
Which two statements are correct regarding the Parent-Child configuration?
- A. A Parent-Child cannot be configured between an Ads data stream type and a Conversion Tag one.
- B. Parent-Child configurations can cause performances issues
- C. Parent-Child allows sharing both dimensions and measurements
- D. Parent-Child links different tables based on shared key values
Answer: B,D
Explanation:
Parent-Child configurations in Marketing Cloud Intelligence are used to link different data tables based on shared key values, allowing for the relational organization of data across variousstreams. While this setup enhances data analysis and reporting by maintaining logical relationships between parent and child tables, it can also introduce performance issues. The complexity increases with the number of relationships and the volume of data, potentially slowing down query processing and data manipulation. Additionally, Parent-Child configurations facilitate the sharing of dimensions and measurements across linked tables, enhancing the data's usability without duplicating it.
NEW QUESTION # 58
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