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Salesforce AP-215 Exam Syllabus Topics:

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

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AP-215 Exam Questions & Answers: Marketing Cloud Intelligence Accredited Professional & AP-215 Exam Braindumps

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Salesforce Marketing Cloud Intelligence Accredited Professional Sample Questions (Q22-Q27):

NEW QUESTION # 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?

Answer: B

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 # 23
What are two potential reasons for performance issues (when loading a dashboard) when using the CRM data stream type?

Answer: B,C

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 # 24
What are unstable measurements?

Answer: D

Explanation:
Unstable measurements refer to metrics that are not aggregated in a standard manner across different grains of data, which can result in inconsistent or unpredictable results when reporting across different dimensions or time frames.
Option C describes a scenario where measurements have manual (Not Auto) aggregation settings, meaning they do not automatically adjust to the aggregation level of the report. Combined with a Granularity setting of 'None', this can lead to instability because the metric isn't bound to a specific granularity, which can cause data inconsistencies or misinterpretations when analyzed at varying levels of detail.


NEW QUESTION # 25
A client Ingested the following We into Marketing Cloud Intelligence:

The mapping of the above file can be seen below:
Date - Day
Media Buy Key - Media Buy Key
Campaign Name - Campaign Name
Campaign Group -. Campaign Custom Attribute 01
Clicks -> Clicks
Media Cost -> Media Cost
Campaign Planned Clicks -> Delivery Custom Metric 01
The client would like to have a "Campaign Planned Clicks" measurement.
This measurement should return the "Campaign Planned Clicks" value per Campaign, for example:
For Campaign Name 'Campaign AAA", the "Campaign Planned Clicks" should be 2000, rather than 6000 (the total sum by the number of Media Buy keys).
In order to create this measurement, the client considered multiple approaches. Please review the different approaches and answer the following question:

Which two options will yield a false result:

Answer: D,E

Explanation:
The goal is to obtain a "Campaign Planned Clicks" value per Campaign, not accumulated by Media Buy keys. Option 1 (SUM aggregation function) would sum all the "Campaign Planned Clicks" across Media Buy keys which would not yield the unique value per Campaign. Similarly, Option 5 (AVG aggregation function at Campaign Key level) would incorrectly average the values. Both options do not provide a way to return a singular "Campaign Planned Clicks" value for each Campaign.


NEW QUESTION # 26
An implementation engineer is requested to extract the second position
of the Campaign Name values.
The Campaign values consist of multiple delimiter types, as can be
seen in the following example:
Campaign Name: Ad15X2w&Delux_wal90
Desired value: Delux
Which three harmonization methods will achieve the desired outcome?

Answer: A,D,E

Explanation:
To extract specific elements from a string in Marketing Cloud Intelligence, such as the second position of a Campaign Name with multiple delimiters, several harmonization methods can be employed:
Calculated Dimensions: These allow for the creation of custom dimensions using expressions or formulas that manipulate existing data. A calculated dimension can be designed to parse and extract segments of a string based on delimiters.
Patterns: This method involves defining a pattern or regex (regular expression) that matches and isolates the desired portion of the string. Patterns are highly effective for strings with complex structures and varying delimiter types.
Mapping Formula: Similar to calculated dimensions, mapping formulas provide a way to apply a transformation or extraction rule to data fields directly within data streams, enabling targeted data extraction like the desired 'Delux' from the Campaign Name.
These methods enable the implementation engineer to accurately segment and extract the needed data from complex string fields efficiently.


NEW QUESTION # 27
......

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