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| Section | Weight | Objectives |
|---|---|---|
| Data Integration and Ingestion | 12% | - Refresh schedules and data flow - API and file-based import - Data streams and connectors |
| General Functionalities | 13% | - Basic concepts and terminology - Core platform capabilities - Navigation and interface |
| Calculated Fields and Functions | 5% | - Custom calculations - VLOOKUP and FUZZYVLOOKUP - Extract and transformation formulas |
| Automation and Workflow | 5% | - Automated distribution - Workflow setup |
| Data Mapping and Modeling | 5% | - Data structure and relationships - Dimensions and measures - Source of truth configuration |
| Performance and Troubleshooting | 5% | - Common issues and fixes - Monitoring and optimization |
| Dashboards and Visualization | 15% | - Chart types and usage - KPI and metric display - Dashboard design and layout |
| Overarching Entities | 3% | - Structure and configuration - Use cases and application scenarios |
| Datasets and Data Views | 10% | - Dataset creation and management - View configuration and sharing - Filtering and segmentation |
| Data Harmonization | 3% | - Cross-source alignment - Standardization methods - Pros and cons of harmonization approaches |
| Reporting and Analytics | 12% | - Insight generation and interpretation - Report creation and scheduling - Attribution models |
| Data Permissions and Governance | 5% | - Data update controls - Parent-child data setups - User access and roles |
| Data Quality and Cleansing | 7% | - Error handling and correction - Validation rules - Duplicate management |
Your client provided the following sources:
Source 1:
Source 2:
Source 3:
As can be seen, the Product values present in sources 2 and 3 are similar and can be linked with the first extraction from 'Media Buy Name' in source1 The end goal is to achieve a final view of Product Group alongside Clicks and Sign Ups, as described below:
Which two options will meet the client's requirement and enable the desired view?
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Your client would like to create a new harmonization field - Exam Topic.
The below table represents the harmonization logic from each source.
As can be seen from the table there are in fact two fields that hold a certain connection: Exam ID and Exam Topic. The connection indicates that where an Exam ID is found -a single Exam Topic value is associated with it.
The Client has a requirement to be able to view measurements from all data sources sliced by Exam Topic values as seen in the following example:
Which harmonization feature should an Implementation engineer use to meet the client's requirement?
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A client Ingested the following We into Marketing Cloud Intelligence:
The mapping of the above file can be seen below:
Date - Day
Media Buy Key - Media Buy Key
Campaign Name - Campaign Name
Campaign Group -. Campaign Custom Attribute 01
Clicks -> Clicks
Media Cost -> Media Cost
Campaign Planned Clicks -> Delivery Custom Metric 01
The client would like to have a "Campaign Planned Clicks" measurement.
This measurement should return the "Campaign Planned Clicks" value per Campaign, for example:
For Campaign Name 'Campaign AAA", the "Campaign Planned Clicks" should be 2000, rather than 6000 (the total sum by the number of Media Buy keys).
In order to create this measurement, the client considered multiple approaches. Please review the different approaches and answer the following question:
Which two options will yield a false result:
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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
"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 January (entire month). What is the number of opportunities in the Interest stage?
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What are two potential reasons for performance issues (when loading a dashboard) when using the CRM data stream type?
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