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| Section | Objectives |
|---|---|
| Data Harmonization and Data Model | - Dimensions and Measures
|
| Reports and Activation | - Report Types
|
| Data Integration and Configuration | - Data Stream Types
|
| Data Visualization and Dashboards | - Filters and Drill-Downs
|
| Marketing Intelligence Platform Fundamentals | - Platform Overview
|
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NEW QUESTION # 14
The following file was uploaded into Marketing Cloud Intelligence as a generic dataset type:
The mapping is as follows:
Day - Day
Web_site_source - Main Generic Entity Attribute 01
Page Views - Generic Metric 1
*Note that 'web_site_key' and 'web_site_name' are NOT mapped.
How many rows will be stored in Marketing Cloud Intelligence after the above file is ingested?
Answer: A
Explanation:
In Marketing Cloud Intelligence, when a file is uploaded as a generic dataset type and mapped accordingly, each unique combination of the mapped fields results in a separate row in the database. The file in question has been mapped with 'Day' to 'Day', 'Web_site_source' to 'Main Generic Entity Attribute 01', and 'Page Views' to 'Generic Metric 1'. The 'web_site_key' and 'web_site_name' are not mapped and thus, won't affect the row count.
Since there are 4 unique combinations of the mapped fields in the uploaded file (each day and source combination is unique), Marketing Cloud Intelligence will store 4 rows after ingestion, corresponding to each unique combination of 'Day' and 'Web_site_source'.
NEW QUESTION # 15
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 source1 The 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?
Answer: A,B
Explanation:
To achieve a final view of Product Group alongside Clicks and Sign Ups, we should use:
Option A:
Custom Classification: By using a Custom Classification key populated with the extraction of the Media Buy Name in Source 1, we can then map 'Product' in Source 2 to this key and 'Product Group' to a Custom Classification level. This will allow for grouping and analysis by Product Group, as well as enable the desired view to be created.
Option D:
Harmonization Center: With patterns from Sources 1 and 3, we can create a harmonized dimension 'Product'. Then, by applying a Data Classification rule using Source 2, we can enhance the harmonized dimension. This allows us to align 'Product Group' with the 'Product' from Sources 1 and 3, facilitating an integrated view of Clicks and Sign Ups by Product Group.
NEW QUESTION # 16
What is the relationship between "Media Buy Key" and "Campaign Key"?
Answer: A
Explanation:
Typically, 'Campaign Key' is a unique identifier for a specific marketing campaign, while 'Media Buy Key' refers to the purchases of advertising space associated with that campaign. A campaign can have multiple media buys, so the relationship is many-to-one, with many media buys (Media Buy Keys) associated with a single campaign (Campaign Key).
NEW QUESTION # 17
A client has integrated data from Facebook Ads, Twitter Ads, and Google Ads in Marketing Cloud Intelligence. For each data source, the data follows a naming convention as shown below:
Facebook Ads Naming Convention - Campaign Name:
Camp|D_CampName#Market_Objective#TargetAge_TargetGender
Twitter Ads Naming Convention - Media Buy Name:
Market|TargetAge|Objective|OrderID
' 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.
In addition to the previous details, the client provides the following data sample:
Logic specification:
If a value is not present in the Validation List, return "Not Valid"
If a value is not present in the Classification File, return "Unclassified".
If the Harmonization center is used to harmonize the above data and files, what table will show the final output?
Answer: C
Explanation:
The correct table would be Option B.
The harmonization process would identify the 'Market' from the campaign or media buy name based on the delimiter and position rules specified in the naming conventions. The harmonized 'Market' would then be matched against the classification file and validation list. If a value does not match the validation list, it would return 'Not Valid', and if it's not present in the classification file, it would return 'Unclassified'. Option B is the only table showing the 'Not Valid' category which aligns with the logic specification provided.
NEW QUESTION # 18
An implementation engineer has been provided with 4 different source files: 03m 16s
1. Twitter Ads
2. Creative Classification
3. Placement Classification
4, Campaign Category Classification
The main source is Twitter Ads (which includes various fields and KPIs), and the rest are classification files that connect to Twitter Ads and enrich different fields within it.
The connections between the files are described as follows:
1st Party Creative Classification
File structure/headers:
Creative ID - links back to Creative Key (Twitter Ads)
1st Party Placement Classification &
File structure/headers:
Category - links back to Campaign Category (Twitter Ads)
Which proposed solution meets the client's requirements for the above use case?
Answer: B
Explanation:
For the given use case, where the Twitter Ads data stream needs to be enriched with classifications from three other sources, the correct implementation would involve creating links between the various fields across these files.
Option A is correct because it shows the correct usage of the fields from the classification files:
"Creative ID" in the Creative Classification file is linked to the "Creative Key" in the Twitter Ads data, allowing for enrichment with creative details.
"Placement ID" in the Placement Classification file is linked to a corresponding field in the Twitter Ads data, allowing for placement details to be added.
"Category" in the Campaign Category Classification file is linked back to "Campaign Category" in the Twitter Ads data, thus enriching the campaign data with the correct categories.
This configuration correctly uses VLOOKUP to enrich the Twitter Ads data stream with additional details from the classification files, aligning with best practices for data integration and enrichment in Marketing Cloud Intelligence.
NEW QUESTION # 19
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