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| Section | Weight | Objectives |
|---|---|---|
| Performance and Troubleshooting | 5% | - Common issues and fixes - Monitoring and optimization |
| Data Integration and Ingestion | 12% | - Data streams and connectors - Refresh schedules and data flow - API and file-based import |
| Data Quality and Cleansing | 7% | - Duplicate management - Validation rules - Error handling and correction |
| Data Permissions and Governance | 5% | - Data update controls - Parent-child data setups - User access and roles |
| Reporting and Analytics | 12% | - Attribution models - Report creation and scheduling - Insight generation and interpretation |
| General Functionalities | 13% | - Navigation and interface - Core platform capabilities - Basic concepts and terminology |
| Data Mapping and Modeling | 5% | - Data structure and relationships - Dimensions and measures - Source of truth configuration |
| Overarching Entities | 3% | - Use cases and application scenarios - Structure and configuration |
| Automation and Workflow | 5% | - Automated distribution - Workflow setup |
| Dashboards and Visualization | 15% | - Chart types and usage - Dashboard design and layout - KPI and metric display |
| Datasets and Data Views | 10% | - Filtering and segmentation - View configuration and sharing - Dataset creation and management |
| Calculated Fields and Functions | 5% | - Extract and transformation formulas - Custom calculations - VLOOKUP and FUZZYVLOOKUP |
| Data Harmonization | 3% | - Cross-source alignment - Pros and cons of harmonization approaches - Standardization methods |
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NEW QUESTION # 20
What are two potential reasons for performance issues (when loading a dashboard) when using the CRM data stream type?
Answer: A,B
Explanation:
For performance issues when loading a dashboard using CRM data stream type:
Pacing can create performance issues because daily rows for every lead and opportunity key can result in a very large number of rows, increasing load times.
Having only calculated measurements means there are no direct, mappable values to query against, which can increase the computational load and affect performance.
NEW QUESTION # 21
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: C
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 # 22
A client's data consists of three data streams as follows:
Data Stream A:
The data streams should be linked together through a parent-child relationship.
Out of the three data streams, Data Stream C is considered the source of truth for both the dimensions and measurements.
The client would like to have a "Site Revenue" measurement.
This measurement should return the highest revenue value per Site, for example:
For Site Key 'SK_C_2', the "Site Revenue" should be $7.00.
When aggregated by date, the "Site Revenue" measurement should return the total sum of the results of all sites.
For example:
For the date 1 Apr 2020, "Site Revenue" should be $11.00 (sum of Site Revenue for Site Keys 'SK_C_1' ($4.00) and 'SK_C_2' ($7.00))
Which options will yield the desired result;
Answer: A
Explanation:
Option #2: It suggests using the 'SUM' function to aggregate the 'Site Revenue' for each 'Site Key'. This is necessary to ensure that when aggregated by date, 'Site Revenue' should return the total sum of the highest revenue for all sites.
Option #4: It indicates changing the Aggregation Function of Revenue to 'MAX' within Data Stream C.
This ensures that for a given 'Site Key', the highest revenue value is selected, which is correct for individual site revenue determination.
Combining Option #2 and Option #4 will provide the desired result:
For an individual 'Site Key', it will give the highest revenue (using MAX aggregation in Option #4).
When aggregating by date across all 'Site Key's, it will sum the highest revenues (using the SUM function in Option #2).
NEW QUESTION # 23
An implementation engineer has been provided with 4 different source files: 03m 48s
1. Twitter Ads ~
2. Creative Classification
3. Placement Classification
4, Campaign Category Classification
The main source is Twitter Ads (which includes various fields and KPIs), and the rest are classification files that connect to Twitter Ads and enrich different fields within it.
The connections between the files are described as follows:
1st Party Creative Classification
File structure/headers:
Creative ID - links back to Creative Key (Twitter Ads)
1st Party Placement Classification by
File structure/headers:
Answer: A
Explanation:
In Salesforce Marketing Cloud Intelligence, connections between source files and classification files are established through common keys that link data records. For this scenario:
The "1st Party Creative Classification" file has a "Creative ID" field which corresponds to the "Creative Key" in the "Twitter Ads" data. This link enables enrichment of Twitter Ads data with creative classification details.
The "1st Party Placement Classification" file will contain a "Placement ID" that connects to a corresponding field in the "Twitter Ads" data, enabling the enrichment of placement classification details.
Option A appears to accurately depict this setup where data streams for "Creative Classification" and "Placement Classification" are connected to the "Twitter Ads" data stream using the "Creative ID" and "Placement ID", respectively. This structure allows for the enhancement of the main Twitter Ads data with additional classification information.
NEW QUESTION # 24
A client's data consists of three data streams as follows:
* The data streams should be linked together through a parent-child relationship.
* Out of the three data streams, Data Stream C is considered the source of truth for both the dimensions and measurements.
Which data stream should be set as a parent?
Answer: A
Explanation:
Since Data Stream C is considered the source of truth for both dimensions and measurements, it should be set as the parent data stream. This is because the parent data stream is used as the primary source for hierarchical and attribute data within a parent-child relationship setup. As the source of truth, Data Stream C will provide the foundational data upon which the other streams can be aligned and will ensure consistency and accuracy across the linked data.
NEW QUESTION # 25
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