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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Data Integration and Ingestion | 12% | - Data streams and connectors - Refresh schedules and data flow - API and file-based import |
| Topic 2: Dashboards and Visualization | 15% | - KPI and metric display - Chart types and usage - Dashboard design and layout |
| Topic 3: Performance and Troubleshooting | 5% | - Monitoring and optimization - Common issues and fixes |
| Topic 4: General Functionalities | 13% | - Navigation and interface - Basic concepts and terminology - Core platform capabilities |
| Topic 5: Data Permissions and Governance | 5% | - Data update controls - Parent-child data setups - User access and roles |
| Topic 6: Data Quality and Cleansing | 7% | - Duplicate management - Error handling and correction - Validation rules |
| Topic 7: Datasets and Data Views | 10% | - Filtering and segmentation - Dataset creation and management - View configuration and sharing |
| Topic 8: Calculated Fields and Functions | 5% | - VLOOKUP and FUZZYVLOOKUP - Extract and transformation formulas - Custom calculations |
| Topic 9: Data Mapping and Modeling | 5% | - Source of truth configuration - Data structure and relationships - Dimensions and measures |
| Topic 10: Reporting and Analytics | 12% | - Insight generation and interpretation - Report creation and scheduling - Attribution models |
| Topic 11: Automation and Workflow | 5% | - Workflow setup - Automated distribution |
| Topic 12: Data Harmonization | 3% | - Standardization methods - Cross-source alignment - Pros and cons of harmonization approaches |
| Topic 13: Overarching Entities | 3% | - Structure and configuration - Use cases and application scenarios |
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NEW QUESTION # 21
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
A pivot table was created to present the count of opportunities in each stage. The pivot table is filtered on Jan 7th - 11th. Which option reflects the stage(s) the Opportunity key 123AA01 is associated with?
Answer: C
Explanation:
Analyzing the Opportunity file with a filter set from January 7th to 11th, Opportunity Key '123AA01' appears under 'Interest' on January 6th and 8th, and under 'Registered' on January 10th. Therefore, during the specified date range, Opportunity Key '123AA01' is associated with both 'Interest' and 'Registered' stages. Salesforce Marketing Cloud Intelligence provides the capability to map and track opportunity stages over time, allowing for historical stage tracking and reporting. This answer aligns with the ability to use pivot tables to filter and display data by specific attributes and timeframes, as outlined in the Salesforce Marketing Cloud Intelligence documentation.
NEW QUESTION # 22
The following file was uploaded into Marketing Cloud Intelligence as a generic dataset type:
The mapping is as follows:
Day - Day
Web_site_source - Main Generic Entity Attribute 01
Page Views - Generic Metric 1
*Note that 'web_site_key' and 'web_site_name' are NOT mapped.
How many rows will be stored in Marketing Cloud Intelligence after the above file is ingested?
Answer: C
Explanation:
In Marketing Cloud Intelligence, when a file is uploaded as a generic dataset type and mapped accordingly, each unique combination of the mapped fields results in a separate row in the database. The file in question has been mapped with 'Day' to 'Day', 'Web_site_source' to 'Main Generic Entity Attribute 01', and 'Page Views' to 'Generic Metric 1'. The 'web_site_key' and 'web_site_name' are not mapped and thus, won't affect the row count.
Since there are 4 unique combinations of the mapped fields in the uploaded file (each day and source combination is unique), Marketing Cloud Intelligence will store 4 rows after ingestion, corresponding to each unique combination of 'Day' and 'Web_site_source'.
NEW QUESTION # 23
What Is a disadvantage of using a Vlookup formula?
Answer: C
Explanation:
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.
NEW QUESTION # 24
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: C
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 # 25
A client provides the following two data streams:
Data Stream 1:
The client would like to use a VLOOKUP formula to calculate the Cost per Campaign Advertiser on January 1st 2020.
Which mapping options should the client apply to obtain the expected result?
Answer: C
Explanation:
To calculate Cost per Campaign Advertiser using a VLOOKUP formula, the client needs to look up the 'Cost' from Data Stream 2 based on a matching 'Media Buy Name' in Data Stream 1. Option A shows that 'Media Buy Name' is the lookup value, which is correct. The 'Campaign Advertiser' is then linked to the 'Cost' from Data Stream 2 through the VLOOKUP formula applied to the 'Media Buy Custom Attribute 01' in Data Stream 2. This setup will correctly associate the cost with the campaign advertiser.
NEW QUESTION # 26
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