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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Reporting and Analytics | 12% | - Insight generation and interpretation - Attribution models - Report creation and scheduling |
| Topic 2: Overarching Entities | 3% | - Use cases and application scenarios - Structure and configuration |
| Topic 3: Performance and Troubleshooting | 5% | - Monitoring and optimization - Common issues and fixes |
| Topic 4: Data Harmonization | 3% | - Pros and cons of harmonization approaches - Standardization methods - Cross-source alignment |
| Topic 5: Data Integration and Ingestion | 12% | - Refresh schedules and data flow - API and file-based import - Data streams and connectors |
| Topic 6: General Functionalities | 13% | - Core platform capabilities - Basic concepts and terminology - Navigation and interface |
| Topic 7: Calculated Fields and Functions | 5% | - VLOOKUP and FUZZYVLOOKUP - Custom calculations - Extract and transformation formulas |
| Topic 8: Automation and Workflow | 5% | - Workflow setup - Automated distribution |
| Topic 9: Datasets and Data Views | 10% | - Dataset creation and management - Filtering and segmentation - View configuration and sharing |
| Topic 10: Dashboards and Visualization | 15% | - KPI and metric display - Dashboard design and layout - Chart types and usage |
| Topic 11: Data Quality and Cleansing | 7% | - Validation rules - Duplicate management - Error handling and correction |
| Topic 12: Data Permissions and Governance | 5% | - User access and roles - Parent-child data setups - Data update controls |
| Topic 13: Data Mapping and Modeling | 5% | - Data structure and relationships - Dimensions and measures - Source of truth configuration |
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질문 # 36
Which three statements describe Overarching Entities? 03m 23s
정답：B,D,E
설명：
Overarching Entities in Salesforce Marketing Cloud Intelligence are designed to provide a high level of data organization that spans across multiple data streams. The key points about Overarching Entities are:
B . Relationship Types: Overarching entities can have either a Many-to-Many or One-to-Many relationship with the main entity, which allows for flexible data modeling and relationship definitions based on the nature of the data and how it should be analyzed and reported.
C . Acting as Main Entity: They can serve as a main entity in certain situations, enabling a shift in perspective for data analysis. This can be particularly useful when there is a need to view data from a different dimension that is more aligned with business requirements.
E . Storage Level: The values of these entities are not tied to any single data stream but are maintained at a workspace level, ensuring that they can be applied consistently across different datasets, which is critical for maintaining data integrity and ensuring that classifications are applied uniformly.
질문 # 37
What are two potential reasons for performance issues (when loading a dashboard) when using the CRM data stream type?
정답：A,D
질문 # 38
An implementation engineer has been provided with the below dataset:
*Note: CPC = Cost per Click
Formula: Cost / Clicks
Which action should an engineer take to successfully integrate CPC?
정답：D
설명：
CPC (Cost per Click) is a calculated metric that should be created using a custom measurement based on the formula provided (Cost / Clicks). This calculation does not require a change in the aggregation setting because it is derived from other base metrics that are already aggregated appropriately. In Salesforce Marketing Cloud Intelligence, custom measurements are used to create new metrics from existing data points, and the system will use the underlying data's aggregation to perform the calculation. Reference: Salesforce Marketing Cloud Intelligence documentation on creating custom measurements and calculated metrics.
질문 # 39
An implementation engineer has been asked to perform a QA for a newly created harmonization field, Color, implemented by a client.
The source file that was ingested can be seen below:
The client performed the below standard mapping:
As a final step, the client had created the field 'Color'. As can be seen, it is extracted from the Creative Name (after the '#' sign).
For QA purposes, you have queried a pivot table, with the following fields:
* Media Buy Key
* Media Buy Name
* In View Impressions
The final pivot is presented below:
정답：C
설명：
Given that the 'Color' field is extracted from the 'Creative Name' field and appears to be part of the creative-level data, the most logical method would be to create an EXTRACT formula and map it to a Creative custom attribute. This allows the 'Color' value to be associated directly with each creative entry. In Salesforce Marketing Cloud Intelligence, the EXTRACT formula can be used to parse and segment text strings within a field, and this process is used for harmonizing data by creating new dimensions or attributes based on existing data, which is what's described here. This answer is consistent with Salesforce Marketing Cloud Intelligence features that enable data transformation and harmonization through formulaic mapping, as per the official Salesforce documentation on data harmonization and transformation.
질문 # 40
An implementation engineer is requested to apply the following logic:
To apply the above logic, the engineer used only the Harmonization Center, without any mapping manipulations. What is the minimum amount of Patterns creating both 'Platform' and 'Line of Business'?"
정답：D
설명：
To create both 'Platform' and 'Line of Business' fields using Patterns in the Harmonization Center without mapping manipulations, the engineer would need to create separate patterns for each data source mentioned. According to the provided images:
One pattern for LinkedIn Ads, to extract the 'Campaign Name' at position 4 for the Platform and 'Media Buy Name' at position 7 for Line of Business.
One pattern for AdRoll, to extract 'Media Buy Name' at position 3 for Platform and at position 2 for Line of Business.
One pattern for Google Analytics, which seems not required for the Platform but could apply if the Line of Business extraction is necessary, although it states N/A.
Hence, a minimum of 3 patterns would be necessary to create the fields required.
질문 # 41
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