2025 EXAM QSDA2024 LABS: QLIK SENSE DATA ARCHITECT CERTIFICATION EXAM - 2024 - UNPARALLELED FREE PDF QUIZ QSDA2024

2025 Exam QSDA2024 Labs: Qlik Sense Data Architect Certification Exam - 2024 - Unparalleled Free PDF Quiz QSDA2024

2025 Exam QSDA2024 Labs: Qlik Sense Data Architect Certification Exam - 2024 - Unparalleled Free PDF Quiz QSDA2024

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Qlik Sense Data Architect Certification Exam - 2024 Sample Questions (Q14-Q19):

NEW QUESTION # 14
A data architect needs to upload data from ten different sources, but only if there are any changes after the last reload. When data is updated, a new file is placed into a folder mapped to E:486396169. The data connection points to this folder.
The data architect plans a script which will:
1. Verify that the file exists
2. If the file exists, upload it Otherwise, skip to the next piece of code.
The script will repeat this subroutine for each source. When the script ends, all uploaded files will be removed with a batch procedure. Which option should the data architect use to meet these requirements?

  • A. FilePath, IF, THEN, Drop
  • B. FileSize, IF, THEN, END IF
  • C. FilePath, FOR EACH, Peek, Drop
  • D. FileExists, FOR EACH, IF

Answer: D


NEW QUESTION # 15

Refer to the exhibits.
On executing a load script of an app, the country field needs to be normalized. The developer uses a mapping table to address the issue. The script runs successfully but the resulting table is not correct.
What should the data architect do?

  • A. Use LOAD DISTINCT on the mapping table
  • B. Review the values of the source mapping table
  • C. Use a LEFT JOIN Instead of the APPLYMAP
  • D. Create two different mapping tables

Answer: B

Explanation:
In this scenario, the issue arises from using the applymap() function to normalize the country field values, but the result is incorrect. The reason is most likely related to the values in the source mapping table not matching the values in the Fact_Table properly.
The applymap() function in Qlik Sense is designed to map one field to another using a mapping table. If the source values in the mapping table are inconsistent or incorrect, the applymap() will not function as expected, leading to incorrect results.
Steps to resolve:
* Review the mapping table (MAP_COUNTRY): The country field in the CountryTable contains values such as "U.S.", "US", and "United States" for the same country. To correctly normalize the country names, you need to ensure that all variations of a country's name are consistently mapped to a single value (e.g., "USA").
* Apply Mapping: Review and clean up the mapping table so that all possible variants of a country are correctly mapped to the desired normalized value.
Key References:
* Mapping Tables in Qlik Sense: Mapping tables allow you to substitute field values with mapped values. Any mismatches or variations in source values should be thoroughly reviewed.
* Applymap() Function: This function takes a mapping table and applies it to substitute a field value with its mapped equivalent. If the mapped values are not correct or incomplete, the output will not be as expected.


NEW QUESTION # 16
A data architect needs to develop three separate apps (Sales, Finance, and Operations). The three apps share numerous identical calculation expressions.
The goals include:
* Reducing duplicate script
* Saving time on expression modifications
* Increasing reusable Qlik developer assets.
The data architect creates a common script and stores it on a file server that Qlik Sense can access. How should the data architect complete the requirements?

  • A. Call batch file
  • B. Include script function
  • C. Macro on server
  • D. Execute server script

Answer: B

Explanation:
When developing multiple Qlik Sense applications (Sales, Finance, Operations) that share numerous identical calculation expressions, it is crucial to have a centralized, reusable script to avoid redundancy, save time on modifications, and increase the reusability of the assets.
The best approach in Qlik Sense to achieve these goals is to use theIncludescript function. This function allows the data architect to reference a script file that is stored on a file server. The Include function willinject the contents of the external script file into the Qlik Sense script at the point where the Include statement is called. This means that all three apps (Sales, Finance, Operations) can include this common script, and any updates made to the script will automatically apply to all apps that include it.
This method provides a highly maintainable solution because:
* No Duplicate Script:The shared logic is maintained in a single file, eliminating redundancy.
* Ease of Modifications:Any changes made to the script are propagated to all applications that include it.
* Reusable Assets:The script can be reused across different applications, enhancing efficiency and consistency.


NEW QUESTION # 17

Refer to the exhibit.
What does the expression sum< [orderMetAmount ]) return when all values in LineNo are selected?

  • A. 0
  • B. 1
  • C. 2
  • D. 3

Answer: B

Explanation:
The expression sum([OrderNetAmount]) sums the values in the OrderNetAmount field across the dataset.
Given that the dataset includes an inline table that is joined with another, the expression calculates the sum of OrderNetAmount for all selected rows. In this scenario, all values in LineNo are selected, which doesn't affect the summation of OrderNetAmount because LineNo isn't directly used in the sum calculation.
Step-by-step Calculation:
* The Orders table contains the OrderNetAmount for each order. The values provided are 90, 500, 100, and 120.
* Adding these values together:90+500+100+120=81090 + 500 + 100 + 120 = 81090+500+100+120=810
* However, after the Left Join operation with the OrderDetails table, some of these rows might be duplicated if the join results in multiple matches. But since the field being summed, OrderNetAmount, is from the original Orders table and not affected by the details in OrderDetails, the sum still remains consistent with the original values in the Orders table.
Thus, the sum of OrderNetAmount is 149014901490, based on the combined effects of the original data structure and the join operation.


NEW QUESTION # 18
Exhibit.

A data architect must load the two tables without creating a synthetic key. The data architect also must make sure expressions like Sum([Budgeted Sales]) are calculated correctly.
Which load script meets these requirements?

  • A.
  • B.
  • C.
  • D.

Answer: B

Explanation:
In the scenario provided, the data architect needs to load two tables (Budget and Sales) without creating a synthetic key, while ensuring that expressions like Sum([Budgeted Sales]) are calculated correctly.
Here is a breakdown of the options:
* Option A (Outer Join):This option uses an outer join between the Sales table and the Budget table.
While this approach will combine the tables based on the common fields (Year and Region), it will result in a single table that contains all fields from both tables. This approach prevents the creation of a synthetic key and retains all records from both tables, ensuring that all budgeted and actual sales data is available. As a result, calculations like Sum([Budgeted Sales]) will work correctly.This is the correct solution.
* Option B (Concatenate):This option uses concatenate, which combines the tables by stacking them on top of each other as if they were one table. This approach will not prevent synthetic keys and could cause issues with calculations since Budgeted Sales and Actual Sales would be in the same column, leading to incorrect aggregation results.
* Option C (Separate Load):This option simply loads the tables separately without any join or concatenation. While this will not create a synthetic key, it will result in two separate tables in the data model. Without any connection between these tables, calculations involving both Budgeted Sales and Actual Sales will not work correctly.
* Option D (Inner Join):This option uses an inner join, which will combine only the records that match in both tables based on Year and Region. While this approach avoids synthetic keys, it may exclude records that do not have a corresponding match in both tables, potentially leading to incomplete data.
Given the requirements to avoid synthetic keys and ensure correct calculations,Option A (Outer Join)is the most appropriate approach. It ensures all relevant data is included and that the data model remains free from synthetic keys, while also allowing accurate calculations.


NEW QUESTION # 19
......

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