AP-215日本語認定 & AP-215試験攻略

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Salesforce AP-215 Exam Syllabus Topics:

Section	Objectives
Data Integration and Configuration	- Data Ingestion 1. Scheduling and refresh settings 2. File upload and API data sources - Data Stream Types 1. Understanding different data stream types 2. Configuring data source properties - Data Mapping 1. Data model configuration 2. Mapping fields from source files
Reports and Activation	- Data Export 1. Exporting data and insights 2. Integration with external tools - Report Types 1. Report scheduling 2. Standard and custom reports
Marketing Intelligence Platform Fundamentals	- Platform Overview 1. Key features and capabilities 2. Marketing Cloud Intelligence (formerly Datorama) overview - Administration and Security 1. Workspace and account settings 2. User management and permissions
Data Visualization and Dashboards	- Calculated Measurements 1. Formulas and functions 2. Creating custom calculations - Dashboard Design 1. Building dashboards 2. KPI widgets and chart types - Filters and Drill-Downs 1. Drill-down configuration 2. Global and local filters
Data Harmonization and Data Model	- Dimensions and Measures 1. Creating and managing measures (KPIs) 2. Calculated measurements 3. Creating and managing dimensions - Parent-Child Data Streams 1. Linking data streams 2. Data Update Permissions 3. Override Media Buy Hierarchies - Data Classification 1. Attribute classification 2. Hierarchy management

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有益な取引を行うだけでなく、SalesforceユーザーがAP-215証明書を取得するまでの最短時間で試験に合格できるようにしたいと考えています。 AP-215試験のプラクティスを選択すると、PassTest試験の準備に20〜30時間しかかかりません。 AP-215の学習教材は試験の概要とAP-215ガイドの質問の質問に密接に関連しているため、このような短い時間ですべてのコンテンツを終了できるかどうかを尋ねる場合があります。最新の基本的なMarketing Cloud Intelligence Accredited Professional知識に関連しています。 AP-215試験問題に合格した場合のみ、AP-215試験に合格します。

Salesforce Marketing Cloud Intelligence Accredited Professional 認定 AP-215 試験問題 (Q20-Q25):

質問 # 20
Client has provided sample flies 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.
As a first step, a Parent-Child relationship was created between the two files, and the following mapping was performed, within both data streams:

Please note:
* All other measurements were mapped as well to the appropriate fields.
* No other mapping manipulations or formulas were implemented.
How many records will the merged table hold?

A. 0
B. 1
C. 2
D. Depends on the Data Updates Permissions

正解：C

解説：
Since the data sources are linked by shared Media Buy names and all other measurements are mapped to appropriate fields without additional manipulations, each unique Media Buy Name from Google DV360 will pair with its corresponding Media Buy Name in Google Campaign Manager. The number of records in the merged table will equal the number of unique Media Buy Names in Google DV360, provided there is a matching name in Google Campaign Manager. The sample shows 4 unique Media Buy Names in Google DV360, thus resulting in 4 records.

質問 # 21
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?

A. A custom metric and set aggregation to AUTO
B. A separate entity key
C. An attribute of 'Meeting Code'
D. A custom metric and set aggregation to SUM

正解：C

解説：
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.

質問 # 22
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?

A. Populate the logic within a custom measurement. No need to change Aggregation.
B. Populate the logic within a custom measurement. Set Aggregation to AVG.
C. Unmap it, as Datorama will calculate it automatically.
D. Populate the logic within a custom measurement. Set Aggregation to SUM.

正解：A

解説：
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.

質問 # 23
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?

A. LEFT(EXTRACT(csv[campaign_name'}/-',1),3)
B. EXTRACT(csv[campaign_name'],-,0)
C. EXTRACT(EXTRACT(csv['campaign_name]]/@',1),-,0)
D. EXTRACT(csv[campaign_name!;@',1)
E. LEFT(EXTRACT(csy['campaign_name]],~',0),3)

正解：D

解説：
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.

質問 # 24
An implementation engineer has been asked to perform QA for a standard file ingestion, done by the client.
The source file that was ingested can be seen below:

The number of rows added to this data stream is 3. What could have led to this discrepancy?

A. All fields are mapped except for the Media Buy Key.
B. All fields are mapped except for the Creative Name
C. All fields are mapped except for the Campaign Key
D. All fields are mapped except for the Media Buy Name.

正解：C

解説：
The source file shows data related to media buys, including a 'Media Buy Key', 'Media Buy Name', 'Campaign Key', and 'Site Key', among other fields. If only three rows were added, and the discrepancy is due to a missing field, it's likely that 'Campaign Key' is the field not mapped, because it is crucial for linking related records in the data stream. Without the 'Campaign Key', the system cannot associate the media buy data with specific campaigns, leading to a potential loss of data rows during ingestion.

質問 # 25
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