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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Calculated Fields and Functions | 5% | - VLOOKUP and FUZZYVLOOKUP - Extract and transformation formulas - Custom calculations |
| Topic 2: General Functionalities | 13% | - Core platform capabilities - Basic concepts and terminology - Navigation and interface |
| Topic 3: Automation and Workflow | 5% | - Automated distribution - Workflow setup |
| Topic 4: Datasets and Data Views | 10% | - View configuration and sharing - Filtering and segmentation - Dataset creation and management |
| Topic 5: Data Mapping and Modeling | 5% | - Data structure and relationships - Dimensions and measures - Source of truth configuration |
| Topic 6: Data Harmonization | 3% | - Cross-source alignment - Pros and cons of harmonization approaches - Standardization methods |
| Topic 7: Dashboards and Visualization | 15% | - KPI and metric display - Dashboard design and layout - Chart types and usage |
| Topic 8: Data Integration and Ingestion | 12% | - Refresh schedules and data flow - API and file-based import - Data streams and connectors |
| Topic 9: Reporting and Analytics | 12% | - Attribution models - Report creation and scheduling - Insight generation and interpretation |
| Topic 10: Overarching Entities | 3% | - Structure and configuration - Use cases and application scenarios |
| Topic 11: Data Permissions and Governance | 5% | - Data update controls - Parent-child data setups - User access and roles |
| Topic 12: Data Quality and Cleansing | 7% | - Error handling and correction - Validation rules - Duplicate management |
| Topic 13: Performance and Troubleshooting | 5% | - Common issues and fixes - Monitoring and optimization |
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NEW QUESTION # 49
A client would like to integrate the following two sources:
Google Campaign Manager:
IAS:
After configuring a Parent-Child relationship between the files, which query should an implementation engineer run in order to QA the setup?
Answer: C
Explanation:
To QA the Parent-Child relationship setup between Google Campaign Manager and IAS data sources, it is essential to query fields that are common to both sources and that are relevant to the relationship. 'Media Buy Type' and 'Media Buy Name' are common identifiers between the two datasets. 'Impressions' from the Google Campaign Manager and 'Analyzed Impressions' from the IAS data are the metrics that should be compared to ensure they match or correlate as expected due to the Parent-Child relationship. The QA process involves checking that the data is correctly aligned and that the metrics from the parent source (Google Campaign Manager) are properly related to the metrics from the child source (IAS). Reference: Salesforce Marketing Cloud Intelligence documentation on data integration, Parent-Child relationships, and QA procedures for data setup.
NEW QUESTION # 50
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:
The client suggested to create, without any mapping manipulations, several patterns via the harmonization center that will generate two Harmonized Dimensions:
Exam ID
Exam Topic
Given the above information, which statement is correct regarding the ability to implement this request with the above suggestion?
Answer: C
Explanation:
If the harmonization logic consistently associates a single Exam Topic with each Exam ID across all data sources, then creating two harmonized dimensions may be unnecessary. One harmonized dimension for Exam Topic would suffice because it inherently carries the Exam ID's uniqueness within it. The harmonized dimension for Exam Topic would allow the client to slice the data by Exam Topic values, fulfilling the requirement.
NEW QUESTION # 51
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?
Answer: A
Explanation:
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.
NEW QUESTION # 52
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?
Answer: C
Explanation:
Based on the Opportunity file, the Opportunity Stage of 'Interest' occurs 3 times across unique Opportunity Keys. Since the pivot table is filtered to present the entire month of January and the Opportunity Stage 'Interest' is listed three times with different Opportunity Keys, the count of opportunities in the 'Interest' stage would be 3.
NEW QUESTION # 53
An Implementation engineer is requested to create a new harmonization field 'Offer' and apply the following logic:
The implementation engineer to use the Harmonization Center. Which of the below actions can help implement the new dimension 'Offer?
Answer: B
Explanation:
To implement the new harmonization field 'Offer', the implementation engineer would create two separate harmonization patterns for LinkedIn and AdRoll sources, extracting the 'Campaign Name' using the specified delimiter and position. Then, within Google Analytics' mapping, a custom attribute for the 'Campaign' would be created to apply the formula logic based on the source. This allows for the harmonization of campaign data across different platforms, ensuring consistency in the reporting and analysis within Marketing Cloud Intelligence. The total patterns required would be three, one for each data source involved.
NEW QUESTION # 54
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