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| Section | Weight | Objectives |
|---|---|---|
| Datasets and Data Views | 10% | - Dataset creation and management - Filtering and segmentation - View configuration and sharing |
| General Functionalities | 13% | - Navigation and interface - Core platform capabilities - Basic concepts and terminology |
| Calculated Fields and Functions | 5% | - VLOOKUP and FUZZYVLOOKUP - Custom calculations - Extract and transformation formulas |
| Data Permissions and Governance | 5% | - Parent-child data setups - User access and roles - Data update controls |
| Automation and Workflow | 5% | - Workflow setup - Automated distribution |
| Reporting and Analytics | 12% | - Report creation and scheduling - Attribution models - Insight generation and interpretation |
| Dashboards and Visualization | 15% | - Chart types and usage - KPI and metric display - Dashboard design and layout |
| Overarching Entities | 3% | - Use cases and application scenarios - Structure and configuration |
| Data Harmonization | 3% | - Pros and cons of harmonization approaches - Cross-source alignment - Standardization methods |
| 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% | - Duplicate management - Error handling and correction - Validation rules |
| Data Mapping and Modeling | 5% | - Source of truth configuration - Data structure and relationships - Dimensions and measures |
AP-215試験に簡単に合格し、最短時間で認定資格を取得したい場合、最良の方法は、最高品質のAP-215試験準備資料を購入することです。それが私たちのすることです。 AP-215トレーニング資料は、この分野で高い合格率を誇ることで有名です。当社の製品を選択した場合、AP-215試験を100％クリアできると確信しています。確実に試験に合格する方法についてまだ頭痛の種である場合、AP-215模擬試験の質問が最良の選択です。 heしないで、私たちを選んでください！
質問 # 14
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;
正解：D
解説：
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).
質問 # 15
An implementation engineer is requested to apply the following logic:
To apply the above logic, the engineer used only the Harmonization Center, without any mapping manipulations. What is the minimum amount of Patterns creating both 'Platform' and 'Line of Business'?"
正解：B
解説：
To create both 'Platform' and 'Line of Business' fields using Patterns in the Harmonization Center without mapping manipulations, the engineer would need to create separate patterns for each data source mentioned. According to the provided images:
One pattern for LinkedIn Ads, to extract the 'Campaign Name' at position 4 for the Platform and 'Media Buy Name' at position 7 for Line of Business.
One pattern for AdRoll, to extract 'Media Buy Name' at position 3 for Platform and at position 2 for Line of Business.
One pattern for Google Analytics, which seems not required for the Platform but could apply if the Line of Business extraction is necessary, although it states N/A.
Hence, a minimum of 3 patterns would be necessary to create the fields required.
質問 # 16
What Is a disadvantage of using a Vlookup formula?
正解：D
解説：
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.
質問 # 17
An implementation engineer has been asked to perform a QA for a newly created harmonization field, Color, implemented by a client.
The source file that was ingested can be seen below:
The client performed the below standard mapping:
As a final step, the client had created the field 'Color'. As can be seen, it is extracted from the Creative Name (after the '#' sign).
For QA purposes, you have queried a pivot table, with the following fields:
* Media Buy Key
* Media Buy Name
* In View Impressions
The final pivot is presented below:
正解：A
解説：
Given that the 'Color' field is extracted from the 'Creative Name' field and appears to be part of the creative-level data, the most logical method would be to create an EXTRACT formula and map it to a Creative custom attribute. This allows the 'Color' value to be associated directly with each creative entry. In Salesforce Marketing Cloud Intelligence, the EXTRACT formula can be used to parse and segment text strings within a field, and this process is used for harmonizing data by creating new dimensions or attributes based on existing data, which is what's described here. This answer is consistent with Salesforce Marketing Cloud Intelligence features that enable data transformation and harmonization through formulaic mapping, as per the official Salesforce documentation on data harmonization and transformation.
質問 # 18
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" - Main Generic Entity Attribute
"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 Jan 11th. What is the number of 'opportunities in the Confirmed Interest stage?
正解：D
解説：
Based on the data provided and the date filter set to January 11th, there are no records for 'Confirmed Interest' on that specific date in the Opportunity file. Thus, the number of opportunities in the 'Confirmed Interest' stage for January 11th would be zero (0). In Salesforce Marketing Cloud Intelligence, when creating pivot tables, the data is aggregated based on the selected filters. If no records meet the filter criteria, the result for that category would be zero. The answer is supported by best practices in data analysis and reporting within Salesforce Marketing Cloud Intelligence, where date filters are applied to segment and analyze data.
質問 # 19
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