Reliable Qlik QSDA2024 PDF Questions - Pass Exam With Confidence

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Qlik QSDA2024 Exam Syllabus Topics:

Topic	Details
Topic 1	Validation: This section tests data analysts and data architects on how to validate and test scripts and data. It focuses on selecting the best methods for ensuring data accuracy and integrity in given scenarios.
Topic 2	Data Connectivity: This part evaluates how data analysts identify necessary data sources and connectors. It focuses on selecting the most appropriate methods for establishing connections to various data sources.
Topic 3	Identify Requirements: This section assesses the abilities of data analysts in defining key business requirements. It includes tasks such as identifying stakeholders, selecting relevant metrics, and determining the level of granularity and aggregation needed.
Topic 4	Data Transformations: This section examines the skills of data analysts and data architects in creating data content based on specific requirements. It also covers handling null and blank data and documenting Data Load scripts.
Topic 5	Data Model Design: In this section, data analysts and data architects are tested on their ability to determine relevant measures and attributes from each data source.

Qlik Sense Data Architect Certification Exam - 2024 Sample Questions (Q22-Q27):

NEW QUESTION # 22

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: D

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 # 23
Exhibit.

Refer to the exhibits.
The Orders table contains a list of orders and associated details. A data architect needs to replace the SupplierlD with the SupplierName using the second table as the source.
The output must be a single table.
Which script should the data architect use?

Answer: D

Explanation:
In this scenario, the data architect needs to replace the SupplierID in the Orders table with the corresponding SupplierName from the Suppliers table, and the desired output should be a single table that includes all the order details along with the SupplierName instead of the SupplierID.
Analyzing the Options:
* Option A:
* Uses a MAPPING LOAD followed by an APPLYMAP to replace SupplierID with SupplierName in the Orders table. However, the table is dropped afterward, which means it won't produce the required output.
* The MAPPING LOAD approach is generally used to map values but is not necessary in this context as we are combining data from two tables directly.
* Option B:
* This option attempts to LEFT JOIN the Products table with the Suppliers table, but it does not directly address replacing SupplierID with SupplierName in the Orders table.
* Additionally, it does not remove the SupplierID after the join, which is essential for the correct output.
* Option C:
* This option uses a LEFT JOIN with the DISTINCT keyword on the SupplierID field to avoid duplicates. The SupplierName is correctly joined to the Orders table, replacing the SupplierID.
* This approach is the most appropriate because it results in a single table containing all order details with the SupplierName instead of the SupplierID.
* Option D:
* Similar to Option A, but it also introduces an unnecessary renaming step with MAPPING LOAD.
It's redundant and does not improve the solution over Option C.
Correct Script Choice:
Option Cis the correct script because:
* It ensures that SupplierName replaces SupplierID in the Orders table using a LEFT JOIN.
* The DISTINCT keyword is applied to the SupplierID field to prevent duplicate rows during the join.
* The result is a single table containing the required information with SupplierName in place of SupplierID.
References:
* Qlik Sense Join Operations: Using the correct JOIN type and ensuring proper deduplication (with DISTINCT if necessary) is key to merging tables in Qlik Sense.

NEW QUESTION # 24
A data architect executes the following script:

Which values does the OrderDate field contain after executing the script?

A. 20210131, 2020/01/31, 31/01/2019, 0
B. 20210131, 2020/01/31, 31/01/2019, 31/12/2022
C. 20210131, 2020/01/31, 31/01/2019
D. 20210131, 2020/01/31, 31/01/2019, 9999

Answer: B

Explanation:
In the script provided, the alt() function is used to handle various date formats. The alt() function in Qlik Sense evaluates a list of expressions and returns the first valid expression. If none of the expressions are valid, it returns the last argument provided (in this case, '31/12/2022').
Step-by-step breakdown:
* The alt() function checks the Date field for three different formats:
* YYYYMMDD
* YYYY/MM/DD
* DD/MM/YYYY
* If none of these formats match the value in the Date field, the default date '31/12/2022' is assigned.
Values in the Date field:
* 20210131: Matches the first format YYYYMMDD.
* 2020/01/31: Matches the second format YYYY/MM/DD.
* 31/01/2019: Matches the third format DD/MM/YYYY.
* 9999: Does not match any of the formats, so the alt() function returns the default value '31/12/2022'.

NEW QUESTION # 25
Refer to the exhibit.

A system creates log files and csv files daily and places these files in a folder. The log files are named automatically by the source system and change regularly. All csv files must be loaded into Qlik Sense for analysis.
Which method should be used to meet the requirements?

Answer: A

Explanation:
In the scenario described, the goal is to load all CSV files from a directory into Qlik Sense, while ignoring the log files that are also present in the same directory. The correct approach should allow for dynamic file loading without needing to manually specify each file name, especially since the log files change regularly.
Here's whyOption Bis the correct choice:
* Option A:This method involves manually specifying a list of files (Day1, Day2, Day3) and then iterating through them to load each one. While this method would work, it requires knowing the exact file names in advance, which is not practical given that new files are added regularly. Also, it doesn't handle dynamic file name changes or new files added to the folder automatically.
* Option B:This approach uses a wildcard (*) in the file path, which tells Qlik Sense to load all files matching the pattern (in this case, all CSV files in the directory). Since the csv file extension is explicitly specified, only the CSV files will be loaded, and the log files will be ignored. This method is efficient and handles the dynamic nature of the file names without needing manual updates to the script.
* Option C:This option is similar to Option B but targets text files (txt) instead of CSV files. Since the requirement is to load CSV files, this option would not meet the needs.
* Option D:This option uses a more complex approach with filelist() and a loop, which could work, but it's more complex than necessary. Option B achieves the same result more simply and directly.
Therefore,Option Bis the most efficient and straightforward solution, dynamically loading all CSV files from the specified directory while ignoring the log files, as required.

NEW QUESTION # 26
A startup company is about have its Initial Public Offering (IPO) on the New York Stock Exchange.
This startup company has used Qlik Sense for many years for data-based decision making for Sales and Marketing efforts, as well as for input into Financial Reporting. The startup's Qlik Sense applications use variables that have different values at different points in time.
Due to the increased rigor required in record keeping for public companies, these variables must be clearly recorded in the script reload logs of the Qlik Sense applications. These logs are refreshed daily.
The data architect wants to have the variables names, with their current values,writteninto the script reload logs. Which script statement should the data architect use?

A. LogDetail
B. Tag
C. REM
D. Trace

Answer: D

Explanation:
In the scenario where the startup company is preparing for an IPO, there is an increased need for meticulous record-keeping, including the recording of variable values used in Qlik Sense applications. The TRACE statement is the most suitable option for logging variable values during script execution.
* TRACE: This statement writes custom messages, including variable values, to the script execution log.
By using TRACE, you can ensure that every reload log contains the names and current values of all relevant variables, providing the necessary transparency and traceability.
For example, the script could include:
TRACE $(VariableName);
This command will output the variable's value in the script log, ensuring it is recorded for audit purposes.

NEW QUESTION # 27
......

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Reliable Qlik QSDA2024 PDF Questions - Pass Exam With Confidence

Qlik QSDA2024 Exam Vce Free, QSDA2024 Valid Exam Vce

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Qlik Sense Data Architect Certification Exam - 2024 Sample Questions (Q22-Q27):

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