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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Data Permissions and Governance | 5% | - Data update controls - User access and roles - Parent-child data setups |
| Topic 2: Calculated Fields and Functions | 5% | - Extract and transformation formulas - VLOOKUP and FUZZYVLOOKUP - Custom calculations |
| Topic 3: Performance and Troubleshooting | 5% | - Common issues and fixes - Monitoring and optimization |
| Topic 4: Data Harmonization | 3% | - Pros and cons of harmonization approaches - Standardization methods - Cross-source alignment |
| Topic 5: Reporting and Analytics | 12% | - Report creation and scheduling - Attribution models - Insight generation and interpretation |
| Topic 6: Overarching Entities | 3% | - Use cases and application scenarios - Structure and configuration |
| Topic 7: Data Mapping and Modeling | 5% | - Source of truth configuration - Dimensions and measures - Data structure and relationships |
| Topic 8: Data Quality and Cleansing | 7% | - Duplicate management - Error handling and correction - Validation rules |
| Topic 9: Automation and Workflow | 5% | - Workflow setup - Automated distribution |
| Topic 10: Dashboards and Visualization | 15% | - Dashboard design and layout - KPI and metric display - Chart types and usage |
| Topic 11: General Functionalities | 13% | - Basic concepts and terminology - Navigation and interface - Core platform capabilities |
| Topic 12: Datasets and Data Views | 10% | - View configuration and sharing - Dataset creation and management - Filtering and segmentation |
| Topic 13: Data Integration and Ingestion | 12% | - Data streams and connectors - Refresh schedules and data flow - API and file-based import |
1. 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 Creative Name
B) All fields are mapped except for the Media Buy Name.
C) All fields are mapped except for the Media Buy Key.
D) All fields are mapped except for the Campaign Key
2. 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 Impressions
The final pivot is presented below:
A) A Harmonized dimension was created via a pattern over the Creative Name.
B) A calculated dimension was created with the formula: EXTRACT([Creative_Namel, #1)
C) An EXTRACT formula (for Color) was written and mapped to a Media Buy custom attribute.
D) An EXTRACT formula (for Color) was written and mapped to a Creative custom attribute.
3. 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) Depends on the Data Updates Permissions
B) 3
C) 4
D) 8
4. 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) Unmap it, as Datorama will calculate it automatically.
C) Populate the logic within a custom measurement. Set Aggregation to SUM.
D) Populate the logic within a custom measurement. Set Aggregation to AVG.
5. 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 2
A 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?
A) Interest & Registered
B) interest
C) Confirmed Interest & Registered
D) Confirmed interest
Solutions:
| Question # 1 Answer: D | Question # 2 Answer: D | Question # 3 Answer: C | Question # 4 Answer: A | Question # 5 Answer: A |
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