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| Section | Weight | Objectives |
|---|---|---|
| Dashboards and Visualization | 15% | - Dashboard design and layout - KPI and metric display - Chart types and usage |
| General Functionalities | 13% | - Navigation and interface - Basic concepts and terminology - Core platform capabilities |
| Data Permissions and Governance | 5% | - Parent-child data setups - User access and roles - Data update controls |
| Reporting and Analytics | 12% | - Report creation and scheduling - Insight generation and interpretation - Attribution models |
| Automation and Workflow | 5% | - Automated distribution - Workflow setup |
| Data Integration and Ingestion | 12% | - API and file-based import - Data streams and connectors - Refresh schedules and data flow |
| Performance and Troubleshooting | 5% | - Monitoring and optimization - Common issues and fixes |
| Data Quality and Cleansing | 7% | - Error handling and correction - Validation rules - Duplicate management |
| Datasets and Data Views | 10% | - Dataset creation and management - View configuration and sharing - Filtering and segmentation |
| Calculated Fields and Functions | 5% | - Custom calculations - VLOOKUP and FUZZYVLOOKUP - Extract and transformation formulas |
| Data Harmonization | 3% | - Standardization methods - Cross-source alignment - Pros and cons of harmonization approaches |
| Overarching Entities | 3% | - Use cases and application scenarios - Structure and configuration |
| Data Mapping and Modeling | 5% | - Source of truth configuration - Data structure and relationships - Dimensions and measures |
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NEW QUESTION # 58
A client wants to integrate their data within Marketing Cloud Intelligence to optimize their marketing insights and cross-channel marketing activity analysis. Below are details regarding the different data sources and the number of data streams required for each source.
What three advantages are gained when using Patterns & Data Classification as the harmonization method for creating the Objective field?
Answer: B,D,E
Explanation:
Patterns & Data Classification in Marketing Cloud Intelligence offer several advantages. These include:
Ease of Maintenance (A): Patterns allow for the standardization of data harmonization processes. Once set up, they can be easily maintained and adjusted as needed, without having to manipulate each data stream individually.
Performance (B): By using patterns, data is classified and standardized at ingestion, which can improve the performance of dashboard page loading because the system does not need to perform complex, on-the-fly calculations or transformations.
Scalability (D): Patterns can be applied across multiple data streams consistently, allowing them to scale with the data. This means that as the amount of data grows or as new data sources are added, the same patterns can be reused, ensuring that the data remains harmonized.
NEW QUESTION # 59
Your client has provided sample files of their data from the following data sources:
Google Campaign Manager
Below are the requirements from the client and additional information:
* The sources are linked to each other by shared Media Buy names.
* In addition to the mutual Media Buys, the sources contain campaign and site values. However, the client would like to see the campaign/site values coming from Google CM and not from Google DV360.
* The source of truth for cost is Google DV360
Which action(s) are needed to take place in order to meet the client's requirement and set Google DV360 as the source of truth for Cost?
Answer: C
Explanation:
To set Google DV360 as the source of truth for cost:
The cost data from Google DV360 should be prioritized, which means ensuring that the 'Cost' field in Google Campaign Manager is not mapped or is mapped with less priority compared to Google DV360.
Given that DV360 is to be the source of truth, you do not want competing cost data from Campaign Manager. Unmapping 'Cost' in Google Campaign Manager prevents conflicting data between the two sources and upholds the integrity of the cost data coming from Google DV360.
NEW QUESTION # 60
Your client is interested in ingested the below file to a new generic data stream type:
The field 'Meeting Code' was mapped to the main entity key. 'How should the 'Room Number' be mapped?
Answer: B
Explanation:
In Marketing Cloud Intelligence, when a field is mapped to the main entity key, other related fields should be mapped as attributes of that key if they provide additional descriptors or details. Since 'Room Number' is related to 'Meeting Code', it would be an attribute of the 'Meeting Code' entity, providing additional context to the meetings without serving as a metric or a separate entity key.
NEW QUESTION # 61
An implementation engineer is requested to extract the first three-letter segment of the Campaign Name values.
For example:
Campaign Name: AFD@Mulop-1290
Desired outcome: AFD
Other examples:
Which formula will return the desired values?
Answer: E
Explanation:
The EXTRACT function is used to split a string based on a delimiter and return the segment at the specified position. The campaign names are structured with the segment of interest followed by an '@' sign. Therefore, the formula needs to extract the segment before the '@'.
The correct formula is: EXTRACT(csv['campaign_name']; '@', 1). This will take the 'campaign_name' field, split it at the '@' sign, and return the first segment (position 1), which is the three-letter code that is required. The other options are incorrect because they do not properly specify the delimiter and the segment position in the way needed to achieve the desired outcome.
NEW QUESTION # 62
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 # 63
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