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| Section | Weight | Objectives |
|---|---|---|
| Datasets and Data Views | 10% | - Filtering and segmentation - View configuration and sharing - Dataset creation and management |
| General Functionalities | 13% | - Core platform capabilities - Navigation and interface - Basic concepts and terminology |
| Performance and Troubleshooting | 5% | - Monitoring and optimization - Common issues and fixes |
| Data Integration and Ingestion | 12% | - Data streams and connectors - Refresh schedules and data flow - API and file-based import |
| Reporting and Analytics | 12% | - Attribution models - Report creation and scheduling - Insight generation and interpretation |
| Overarching Entities | 3% | - Use cases and application scenarios - Structure and configuration |
| Data Quality and Cleansing | 7% | - Validation rules - Duplicate management - Error handling and correction |
| Data Permissions and Governance | 5% | - Parent-child data setups - Data update controls - User access and roles |
| Data Harmonization | 3% | - Standardization methods - Cross-source alignment - Pros and cons of harmonization approaches |
| Automation and Workflow | 5% | - Workflow setup - Automated distribution |
| Dashboards and Visualization | 15% | - Dashboard design and layout - KPI and metric display - Chart types and usage |
| Calculated Fields and Functions | 5% | - Extract and transformation formulas - Custom calculations - VLOOKUP and FUZZYVLOOKUP |
| Data Mapping and Modeling | 5% | - Dimensions and measures - Source of truth configuration - Data structure and relationships |
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NEW QUESTION # 28
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: C
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 # 29
The following file was uploaded into Marketing Cloud Intelligence as a Generic Data Stream type:
The mapping is as follows:
Day - Day
web_site_key -> Main Generic Entity Key
web_site_name -> Main Generic Entity Name
Web_site_source -> Main Generic Entity Attribute 01
Page Views - Generic Metric 1
How many rows will be stored in Marketing Cloud Intelligence after the above file is ingested?
Answer: A
Explanation:
With the uploaded file mapped as a Generic Data Stream type, the unique identifier for a row is the combination of 'Day', 'web_site_key', 'web_site_name', and 'Web_site_source'. As 'Day' is mapped to 'Day', 'web_site_key' to 'Main Generic Entity Key', 'web_site_name' to 'Main Generic Entity Name', and 'Web_site_source' to 'Main Generic Entity Attribute 01', each unique combination of these fields will constitute a separate row.
The provided file has 4 unique combinations of 'Day', 'web_site_key', 'web_site_name', and 'Web_site_source', as each line has a unique 'web_site_key' and 'web_site_name'. Consequently, Marketing Cloud Intelligence will store 4 rows, one for each unique combination.
NEW QUESTION # 30
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: D
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 # 31
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 # 32
A client has integrated data from Facebook Ads. Twitter ads, and Google ads in marketing Cloud intelligence. For each data source, the source, the data follows a naming convensions as ...
Facebook Ads Naming Convention - Campaign Name:
CampID_CampName#Market_Object#object#targetAge_TargetGender
Twitter Ads Naming Convention- Media Buy Name
MarketTargeAgeObjectiveOrderID
Google ads Naming Convention-Media Buy Name:
Buying_type_Market_Objective
The client wants to harmonize their data on the common fields between these two platforms (i.e. Market and Objective) using the Harmonization Center. Given the above information, which statement is correct regarding the ability to implement this request?
wet Me - Given the above information, which statement i 's Correct regarding the ability to implement this request?
Answer: A
Explanation:
Despite the different naming conventions, harmonization is possible using patterns in the Harmonization Center. By extracting the 'Market' and 'Objective' components from the naming conventions of each platform, three separate patterns would be created to map these common fields consistently across the data from Facebook Ads, Twitter Ads, and Google Ads.
NEW QUESTION # 33
......
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