Your client would like to create a new harmonization field - Exam Topic.The below table represents the harmonization logic from each source. As can be seen from the table, there are in fact two fields that hold a certain connection: Exam ID and Exam Topic. The connection indicates that where an Exam ID is found - a single Exam Topic value is associated with it.The client has a requirement to be able to view measurements from all data sources sliced by Exam Topic values, as seen in the following example: The client suggested to create, without any mapping manipulations, several patterns via the harmonization center that will generate twoHarmonized Dimensions:Exam IDExam TopicGiven the above information, which statement is correct regarding the ability to implement this request with the above suggestion?

The Harmonized field for Exam ID is redundant. One Harmonized dimension for Exam Topic is enough for a sustainable and working solution

The above Patterns setup will not work for this use case.

The solution will work - the client will be able to view Exam Topic with Email Sends.

Only if 5 different Patterns are created, from 5 different fields - the solution will work.

The Harmonized field for Exam ID is redundant. One Harmonized dimension for Exam Topic is enough for a sustainable and working solution

A client has provided you with sample files of their data from the following data sources:1.Google Analytics2.Salesforce Marketing CloudThe link between these sources is on the following two fields:Message Send KeyA portion of: web_site_source_keyBelow is the logic the client would like to have implemented in Datorama:For 'web site medium' values containing the word ''email'' (in all of its forms), the section after the ''_'' delimiter in 'web_site_source_key' is a 4 digit number, which matches the 'Message Send Key' values from the Salesforce Marketing Cloud file. Possible examples of this can be seen in the following table:Google Analytics: Salesforce Marketing Cloud: The client's objective is to visualize the mutual key values alongside measurements from both files in a table. In order to achieve this, what steps should be taken?

Within both files, map the desired value to Custom Classification Key as follows Salesforce Marketing Cloud: map entire Message Key to Custom Classification Key. Google Analytics: map the extraction logic to Custom Classification Key.

Create a Web Analytics Site custom attribute and populate it with the extraction logic. Create a Data Fusion between the newly created attribute and the Message Send Key.

Upload the two files and create a Parent-Child relationship between them. The Override Media Buy Hierarchy checkbox is checked in Google Analytics.

Create a Web Analytics Site Source custom attribute and populate it with the extraction logic. Create a Data Fusion between the newly created attribute and the Message Send Key.

Which three statements accurately describe the different data stream types in Marketing Cloud intelligence?

All data stream types consist of at least one entity

Each data stream type has Its own main entity

Each data stream type has its own set of measurements

Every data stream type includes the Medio Buy entity

All data stream types consist of at least one entity

All data stream types share at least one mutual measurement

Each data stream type has Its own main entity

Each data stream type has its own set of measurements

Which two statements are correct regarding the Parent-Child configuration?

Parent-Child configurations can cause performances issues

Parent-Child links different tables based on shared key values

Parent-Child configurations can cause performances issues

A Parent-Child cannot be configured between an Ads data stream type and a Conversion Tag one.

Parent-Child links different tables based on shared key values

Parent-Child allows sharing both dimensions and measurements

A client wants to integrate their data within Marketing Cloud Intelligence to optimize their marketing insights and cross-channel marketing activity analysis. Below are details regarding the different data sources and the number of data streams required for each source. What three advantages are gained when using Patterns & Data Classification as the harmonization method for creating the Objective field?

Performance (Performance when loading a dashboard page)

Processing (processing time when loading relevant data streams)

An implementation engineer is requested to create the harmonization field - MagicianThis field should come from multiple Twitter Ads data streams, and should follow the below logic: Using the Harmonization Center, the engineer created a single Pattern for Campaign Name. What other action should the engineer take to meet the requirements?

Create a second Pattern for Media Buy Name and apply a Classification Rule (with the two values) for the final Harmonized Dimension

Create a second Pattern for Media Buy Name and apply two Classification Rules (one for 'Messi' and another for Ronaldo') for the final Harmonized Dimension.

Create a second Pattern for Media Buy Name

Create a second Pattern for Media Buy Name and add a validation list (with the two values) for the final Harmonized Dimension.

Create a second Pattern for Media Buy Name and apply a Classification Rule (with the two values) for the final Harmonized Dimension

What is the relationship between ''Media Buy Key'' and ''Campaign Key''?

Many-to-one (one Campaign Key has many Media Buy Keys)

One-to-many (one Media Buy Key has many Campaign Keys)

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 2A 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?

Confirmed Interest & Registered

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 ImpressionsThe final pivot is presented below:

An EXTRACT formula (for Color) was written and mapped to a Creative custom attribute.

A Harmonized dimension was created via a pattern over the Creative Name.

A calculated dimension was created with the formula: EXTRACT([Creative_Namel, #1)

An EXTRACT formula (for Color) was written and mapped to a Media Buy custom attribute.

An EXTRACT formula (for Color) was written and mapped to a Creative custom attribute.

An implementation engineer has been asked by a client for assistance with the following problem:The below dataset was ingested: However, when performing QA and querying a pivot table with Campaign Category and Clicks, the value for Type' is 4.What could be the reason for this discrepancy?

The aggregation function is set as AVG

The measurement 'Clicks' is set as a percentage.

A mapping formula was populated, indicating not to bring Type! values.

The aggregation function is set as AVG

The aggregation function is set as LIFETIME

An implementation engineer has been provided with the below dataset: *Note: CPC = Cost per ClickFormula: Cost / ClicksWhich action should an engineer take to successfully integrate CPC?

Populate the logic within a custom measurement. No need to change Aggregation.

Unmap it, as Datorama will calculate it automatically.

Populate the logic within a custom measurement. Set Aggregation to AVG.

Populate the logic within a custom measurement. Set Aggregation to SUM.

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?

Media Buy Type, Media Buy Name, Impressions, Analyzed Impressions

Creative Name, Impressions, Analyzed Impressions

Media Buy Type, Analyzed Impressions

A client has integrated the following files:File A: File B: The client would like to link the two files in order to view the two KPIs ('Tasks Completed' and 'Tasks Assigned) alongside 'Employee Name' and/or'Squad'.The client set the following properties:+ File A is set as the Parent data stream* Both files were uploaded to a generic data stream type.* Override Media Buy Hierarchies is checked for file

* The 'Data Updates Permissions' set for file B is 'Update Attributes and Hierarchy'.When filtering on the entire date range (1-30/8), and querying employee ID, Name and Squad with the two measurements - what will the result look like?A)B)C)D)

Your client is interested in ingesting the below file: The client decided to upload the file to a new generic data stream type and map 'Date' to 'Day' and 'Number of Topics' to a generic custom metric.In regards to the fields 'Meeting Code' and 'Meeting Name', your client is debating several options.Which two options would you recommend in order to avoid data loss?

'Meeting Code' will be mapped to 'Main Generic Entity Key'. 'Meeting Name' will be mapped to 'Main Generic Entity custom attribute'.

Concatenation of both 'Meeting Code' and 'Meeting Name' will be mapped to 'Main Generic Entity Key'. 'Meeting Code' will be mapped to 'Main Generic Entity Attribute 1'. 'Meeting Name' will be mapped to 'Main Generic Entity Attribute 2'.

'Meeting Code' will be mapped to 'Main Generic Entity Key'. 'Meeting Name' will be mapped to 'Main Generic Entity custom attribute'.

'Meeting Code' will be mapped to 'Main Generic Entity Key'. 'Meeting Name' will be mapped to 'Generic Entity 2 Key'.

'Meeting Code' will be mapped to 'Main Generic Entity Attribute 1'. 'Meeting Name' will be mapped to 'Main Generic Entity Attribute 2'.

'Meeting Code' will be mapped to 'Main Generic Entity custom attribute'. 'Meeting Name' will be mapped to 'Generic Entity Key'

Concatenation of both 'Meeting Code' and 'Meeting Name' will be mapped to 'Main Generic Entity Key'. 'Meeting Code' will be mapped to 'Main Generic Entity Attribute 1'. 'Meeting Name' will be mapped to 'Main Generic Entity Attribute 2'.

A client wants to integrate their data within Marketing Cloud Intelligence to optimize their marketing insights and cross-channel marketing activity analysis. Below are details regarding the different data sources and the number of data streams required for each source. When harmonizing the Objective field from within the data stream mapping, which advantage is gained?

Performance (Performance when loading a dashboard page)

An implementation engineer is requested to extract the first three-letter segment of the Campaign Name values.For example:Campaign Name: AFD@Mulop-1290Desired outcome: AFDOther examples: Which formula will return the desired values?

EXTRACT(csv[campaign_name!;@',1)

LEFT(EXTRACT(csy['campaign_name]],~',0),3)

EXTRACT(csv[campaign_name!;@',1)

EXTRACT(csv[campaign_name'],---,0)

EXTRACT(EXTRACT(csv['campaign_name]]/@',1),-,0)

LEFT(EXTRACT(csv[campaign_name'}/---',1),3)

A client provides the following three files:File A: File B: File C: File A was uploaded using the Ads data stream type.The client would like to create this view (data from Files B & C) in Datorama: Which proposed solution would cause a false connection between the two files?

VLOOKUP in Data Stream B. Vlookup will return ''Day'' and ''Installs''

VLOOKUP in Data Stream C. Vlookup will return 'MB Name''

Your client provided the following sources:Source 1: Source 2: Source 3: As can be seen, the Product values present in sources 2 and 3 are similar and can be linked with the first extraction from 'Media Buy Name' in source1The end goal is to achieve a final view of Product Group alongside Clicks and Sign Ups, as described below: Which two options will meet the client's requirement and enable the desired view?

Custom Classification: 1 Source 1: Custom Classification key will be populated with the extraction of the Media Buy Name. Source 2: 'Product' will be mapped to Custom Classification key and 'Product Group' to a Custom Classification level. Exam Timer Source 3: 'Product will be mapped to Custom Classification key. Came

Harmonization Center: Patterns from sources 1 and 3 generate harmonized dimension 'Product'. Data Classification rule, using source 2, is applied on top of the harmonized dimension

Custom Classification: 1 Source 1: Custom Classification key will be populated with the extraction of the Media Buy Name. Source 2: 'Product' will be mapped to Custom Classification key and 'Product Group' to a Custom Classification level. Exam Timer Source 3: 'Product will be mapped to Custom Classification key. Came

Overarching Entities: Source 1: custom classification key will be populated with the extraction of the Media Buy Name. Source 2: 'Product' will be mapped to Product field and 'Product Group' to Product Name. Source 3: 'Product' will be mapped to Product field.

Parent Child: All sources will be uploaded to the same data stream type - Ads. The setup is the following: Source 1: Media Buy Key ---- Media Buy Key, extracted product value --- Media Buy Attribute. Source 2: Product --- Media Buy Key, Product Group ---- Media Buy Attribute. Source 3: Product --- Media Buy Key.

Harmonization Center: Patterns from sources 1 and 3 generate harmonized dimension 'Product'. Data Classification rule, using source 2, is applied on top of the harmonized dimension

What are unstable measurements?

Measurements for which Aggregation Settings are set as 'Not Auto' and Granularity is set as 'None'.

Measurements for which Aggregation Settings are set as 'Auto' and Granularity is set as 'None'.

Measurements that are set with the LIFETIME aggregation function

Measurements for which Aggregation Settings are set as 'Not Auto' and Granularity is set as 'None'.

Measurements for which Aggregation Settings are set as 'Not Auto' and Granularity is set as 'Not Empty'.

What Is a disadvantage of using a Vlookup formula?

Could extend processing time of data streams.

Can return values only from the same data stream type

It cannot be used more than once from the same data stream.

Could extend processing time of data streams.

It allows classifying data only on a basis of mutual entity keys.

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 custom metric and set aggregation to AUTO

A custom metric and set aggregation to SUM

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?

All fields are mapped except for the Media Buy Name.

All fields are mapped except for the Media Buy Key.

All fields are mapped except for the Creative Name

All fields are mapped except for the Media Buy Name.

All fields are mapped except for the Campaign Key

After uploading a standard file into Marketing Cloud intelligence via total Connect, you noticed that the number of rows uploaded (to the specific data stream) is NOT equal to the number of rows present in the source file. What are two resource that may cause this gap?

The source file does not contain the media Buy entity

All mapped Measurements for a given row have values equal to zero

The source file does not contain the media Buy entity

The file does not contain any measurements (dimension only)

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A client's data consists of three data streams as follows:

Data Stream A:

Salesforce Certified Marketing Cloud Intelligence Accredited Professional image Question 1 65691 09232024002818000000

* 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.

Assuming the data was ingested properly and the Parent Child was created correctly according to the client's requirements, what is the total

Impressions value for Campaign Key 'CK_3'?

N-A

100

300

150

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Certified Marketing Cloud Intelligence Accredited Professional: Salesforce Certified Marketing Cloud Intelligence Accredited Professional

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Salesforce Certified Marketing Cloud Intelligence Accredited Professional Practice Tests

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