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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Datasets and Data Views | 10% | - Dataset creation and management - View configuration and sharing - Filtering and segmentation |
| Topic 2: General Functionalities | 13% | - Basic concepts and terminology - Core platform capabilities - Navigation and interface |
| Topic 3: Overarching Entities | 3% | - Use cases and application scenarios - Structure and configuration |
| Topic 4: Dashboards and Visualization | 15% | - KPI and metric display - Chart types and usage - Dashboard design and layout |
| Topic 5: Data Integration and Ingestion | 12% | - Data streams and connectors - Refresh schedules and data flow - API and file-based import |
| Topic 6: Calculated Fields and Functions | 5% | - Custom calculations - Extract and transformation formulas - VLOOKUP and FUZZYVLOOKUP |
| Topic 7: Performance and Troubleshooting | 5% | - Monitoring and optimization - Common issues and fixes |
| Topic 8: Automation and Workflow | 5% | - Workflow setup - Automated distribution |
| Topic 9: Data Harmonization | 3% | - Cross-source alignment - Standardization methods - Pros and cons of harmonization approaches |
| Topic 10: Data Permissions and Governance | 5% | - User access and roles - Data update controls - Parent-child data setups |
| Topic 11: Data Quality and Cleansing | 7% | - Validation rules - Duplicate management - Error handling and correction |
| Topic 12: Reporting and Analytics | 12% | - Insight generation and interpretation - Attribution models - Report creation and scheduling |
| Topic 13: Data Mapping and Modeling | 5% | - Source of truth configuration - Data structure and relationships - Dimensions and measures |
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58. Frage
Which three entities and/or functions can be used in an expression when building a calculated dimension?
Antwort: A,D,E
Begründung:
Calculated dimensions (D) and the VLOOKUP function (A) are not typically used within the expression for a calculated dimension. Calculated dimensions are usually an output, not an input, and VLOOKUP is a function typically used to enrich or connect data, not within the definition of a calculated dimension itself.
Explanation:
In the context of Marketing Cloud Intelligence, when building a calculated dimension, you can typically use:
B). Mapped dimensions: These are dimensions that have been brought into Marketing Cloud Intelligence through the data integration process and have been mapped to a known schema or model.
C). The EXTRACT function: This function can be used to dynamically create dimensions by extracting values from a mapped dimension or measurement.
E). Mapped measurements: Similar to mapped dimensions, these are quantitative data points that have been integrated into the platform and can be referenced in calculations.
59. Frage
What Is a disadvantage of using a Vlookup formula?
Antwort: D
Begründung:
The use of VLOOKUP formulas can increase the processing time of data streams because it requires a lookup operation for each row in the data set. When large volumes of data are involved, or when multiple VLOOKUPs are used, this can significantly impact processing time due to the complexity and computational requirements of matching and retrieving the data.
60. Frage
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" - Main Generic Entity Attribute
"Opportunity Count" - Generic Custom Metric
A pivot table was created to present the count of opportunities in each stage. The pivot table is filtered on Jan 11th. What is the number of 'opportunities in the Confirmed Interest stage?
Antwort: C
Begründung:
Based on the data provided and the date filter set to January 11th, there are no records for 'Confirmed Interest' on that specific date in the Opportunity file. Thus, the number of opportunities in the 'Confirmed Interest' stage for January 11th would be zero (0). In Salesforce Marketing Cloud Intelligence, when creating pivot tables, the data is aggregated based on the selected filters. If no records meet the filter criteria, the result for that category would be zero. The answer is supported by best practices in data analysis and reporting within Salesforce Marketing Cloud Intelligence, where date filters are applied to segment and analyze data.
61. Frage
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?
Antwort: D
Begründung:
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.
62. Frage
A client has integrated data from Facebook Ads. Twitter ads, and Google ads in marketing Cloud intelligence. For each data source, the source, the data follows a naming convensions as ...
Facebook Ads Naming Convention - Campaign Name:
CampID_CampName#Market_Object#object#targetAge_TargetGender
Twitter Ads Naming Convention- Media Buy Name
MarketTargeAgeObjectiveOrderID
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. Given the above information, which statement is correct regarding the ability to implement this request?
wet Me - Given the above information, which statement i 's Correct regarding the ability to implement this request?
Antwort: A
Begründung:
Despite the different naming conventions, harmonization is possible using patterns in the Harmonization Center. By extracting the 'Market' and 'Objective' components from the naming conventions of each platform, three separate patterns would be created to map these common fields consistently across the data from Facebook Ads, Twitter Ads, and Google Ads.
63. Frage
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