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| Section | Weight | Objectives |
|---|---|---|
| Dashboards and Visualization | 15% | - KPI and metric display - Chart types and usage - Dashboard design and layout |
| Overarching Entities | 3% | - Structure and configuration - Use cases and application scenarios |
| Datasets and Data Views | 10% | - Dataset creation and management - Filtering and segmentation - View configuration and sharing |
| Performance and Troubleshooting | 5% | - Common issues and fixes - Monitoring and optimization |
| Automation and Workflow | 5% | - Workflow setup - Automated distribution |
| Data Mapping and Modeling | 5% | - Data structure and relationships - Dimensions and measures - Source of truth configuration |
| Data Permissions and Governance | 5% | - Data update controls - Parent-child data setups - User access and roles |
| Data Quality and Cleansing | 7% | - Validation rules - Error handling and correction - Duplicate management |
| General Functionalities | 13% | - Basic concepts and terminology - Core platform capabilities - Navigation and interface |
| Calculated Fields and Functions | 5% | - VLOOKUP and FUZZYVLOOKUP - Extract and transformation formulas - Custom calculations |
| Reporting and Analytics | 12% | - Insight generation and interpretation - Report creation and scheduling - Attribution models |
| Data Integration and Ingestion | 12% | - Refresh schedules and data flow - Data streams and connectors - API and file-based import |
| Data Harmonization | 3% | - Pros and cons of harmonization approaches - Standardization methods - Cross-source alignment |
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NEW QUESTION # 19
What is the relationship between "Media Buy Key" and "Campaign Key"?
Answer: C
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 # 20
Which three entities and/or functions can be used in an expression when building a calculated dimension?
Answer: A,B,E
Explanation:
Calculated dimensions (D) and the VLOOKUP function (A) are not typically used within the expression for a calculated dimension. Calculated dimensions are usually an output, not an input, and VLOOKUP is a function typically used to enrich or connect data, not within the definition of a calculated dimension itself.
Explanation:
In the context of Marketing Cloud Intelligence, when building a calculated dimension, you can typically use:
B). Mapped dimensions: These are dimensions that have been brought into Marketing Cloud Intelligence through the data integration process and have been mapped to a known schema or model.
C). The EXTRACT function: This function can be used to dynamically create dimensions by extracting values from a mapped dimension or measurement.
E). Mapped measurements: Similar to mapped dimensions, these are quantitative data points that have been integrated into the platform and can be referenced in calculations.
NEW QUESTION # 21
Source 3:
Via the harmonization Center, the Client has created Patterns and applied a classification rule using source 2.
While performing QA, you have spotted that the final value of clicks for Product Group Ais 10, where it should've been i5.
How can an implementation engineer fix this discrepancy?
Answer: C
Explanation:
Case Sensitivity Issue:
The discrepancy in the "Clicks" value for Product Group A (10 instead of 15) likely arises from a mismatch caused by case sensitivity in the classification rules. If some data entries use different capitalization (e.g., "Product Group A" vs. "product group a"), the system might treat them as distinct entries, leading to incorrect aggregations.
Solution:
By unchecking the "Case Sensitive" checkbox, the harmonization process will treat entries with different capitalization as the same value. This ensures consistent classification and resolves discrepancies in aggregated metrics like "Clicks."
NEW QUESTION # 22
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?
Answer: B
Explanation:
With File A uploaded using the Ads data stream type, the client wishes to create a view incorporating data from Files B & C.
A false connection would occur if VLOOKUP in Data Stream B is used incorrectly to return "Day" and "Installs". In this scenario, VLOOKUP might inaccurately link data based on MB Name between File B and File A or File C, which do not have a "Day" field to correctly join on. Moreover, "Installs" data in File B doesn't exist, so VLOOKUP cannot correctly return this information. The correct method would be to use the "Media Buy New Name" to link File B and File C since they both have this field, ensuring accurate connection and avoiding data mismatches or false connections.
NEW QUESTION # 23
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?
Answer: B
Explanation:
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.
NEW QUESTION # 24
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