Qlik QSDA2024 Qlik Sense Data Architect Certification Exam - 2024 Exam Practice Test

Answer : A

The given Excel spreadsheet has a Region field where the region value is only specified for the first record within each region. The data architect needs to fill in the missing region values for subsequent rows.

Previous() Function: The Previous() function in Qlik Sense returns the value of the expression from the previous row. In this case, it can be used to fill down the Region values so that each row contains the correct region information.

Implementation: The script can be designed to check if the current row's Region value is missing (null). If it is missing, the script can assign the value from the previous row using the Previous() function.

LOAD

If(IsNull(Region), Previous(Region), Region) AS Region,

...

This logic fills in the missing Region values with the value from the preceding row, which effectively resolves the issue shown in the spreadsheet.

Answer : C

In this scenario, users of a published app report incomplete visualizations, but the data architect is unable to replicate the error. This issue affects only one team, suggesting that the problem is related to how data is being restricted or filtered for that specific team.

Section Access: This is a security feature in Qlik Sense that controls user access to specific data within an app. If Section Access is misconfigured, it can restrict access to more records than intended, leading to incomplete visualizations for certain users or teams.

Restricting Too Many Records: If the Section Access is too restrictive, it might limit the data available to the affected users, causing the visualizations to display incomplete information. This could explain why the data architect, who likely has full access, cannot replicate the issue.

Answer : A

In this scenario, the data architect needs to conform the revenue data from Company B to match the data standard of Company A, where $0 is explicitly used to represent journeys without revenue.

Explanation of the Correct Script:

Option A: money(replace(Revenue, chr(32), 0)) AS [Revenue Conformed]

replace(Revenue, chr(32), 0): This part of the expression replaces any spaces (ASCII character code 32) in the Revenue field with 0.

money(...): This function formats the resulting value as currency. Since Company B may have either null values or spaces where 0 should be, this script ensures that any blanks are replaced with 0 and then formatted as currency.

Why Option A is Correct:

Handling Spaces: The replace() function is effective in replacing spaces with 0, conforming to Company A's standard of using $0 for non-revenue journeys.

Handling NULL Values: The money() function is used to ensure the final output is formatted as currency. However, it's important to note that NULL values are not directly handled by the replace() function, which is why it is applied before money() to deal with spaces.

Answer : D

The scenario describes a need to track social media data over the past 10 years, capturing all changes (inserts, updates, deletes) while reloading the data four times a day.

To manage this:

ModificationTime: This field is essential for tracking changes over time. It indicates when a record was last modified, allowing the script to determine whether it needs to insert, update, or delete records.

Primary Key Field: A primary key is crucial for uniquely identifying records. It enables the script to match records in the source with those already loaded, facilitating updates and deletions.

Insert and Update Records: The script should handle both inserting new records and updating existing ones based on the ModificationTime.

Remove Records: If records are deleted in the source, they should also be removed in the Qlik Sense data model to maintain consistency.

This approach ensures that all changes in the social media data are accurately captured and reflected in the Qlik Sense application.

Answer : A

The issue described relates to the incorrect display of month and year values on the x-axis of a chart. The source data has dates in the M/D/YYYY format, and a calculated field named Month-Year was created using this date format.

To correct the issue:

The correct approach is to use the MonthStart() function, which returns the first date of the month for the provided date. This ensures consistency in month-year representation.

The Date() function is then used to format the result of MonthStart() to the desired format of MMM-YYYY (e.g., Feb-2018).

Explanation of the Correct Expression:

MonthStart([Common Date]): This ensures that all dates within a month are treated as the first day of that month, which is critical for accurate monthly aggregation.

Date(..., 'MMM-YYYY'): This formats the result to show just the month and year in the correct format.

Using this expression ensures that the x-axis correctly displays the month-year values.

Answer : C

The goal is to display the aggregated sales for each sales representative, with all aggregations being performed in the script. Option C is the correct choice because it performs the aggregation correctly using a Group by clause, ensuring that the sum of sales for each employee is calculated within the script.

Data Load:

The Data table is loaded first from the Sales table. This includes the OrderID, OrderDate, CustomerID, EmployeeID, and Sales.

Next, the Emp table is loaded containing EmployeeID and EmployeeName.

Joining Data:

A Left Join is performed between the Data table and the Emp table on EmployeeID, enriching the data with EmployeeName.

Aggregation:

The Summary table is created by loading the EmployeeName and calculating the total sales using the sum([Sales]) function.

The Resident keyword indicates that the data is pulled from the existing tables in memory, specifically the Data table.

The Group by clause ensures that the aggregation is performed correctly for each EmployeeName, summarizing the total sales for each employee.

Key Qlik Sense Data Architect Reference:

Resident Load: This is a method to reuse data that is already loaded into the app's memory. By using a Resident load, you can create new tables or perform calculations like aggregation on the existing data.

Group by Clause: The Group by clause is essential when performing aggregations in the script. It groups the data by specified fields and performs the desired aggregation function (e.g., sum, count).

Left Join: Used to combine data from two tables. In this case, Left Join is used to enrich the sales data with employee names, ensuring that the sales data is associated correctly with the respective employee.

Conclusion: Option C is the most appropriate script for this task because it correctly performs the necessary joins and aggregations in the script. This ensures that the dashboard will display the correct aggregated sales per employee, meeting the data architect's requirements.

Answer : B

In Qlik Sense, when a data load script is executed and an error occurs, the script execution is halted immediately, and any tables that were being loaded at the time of the error are discarded. However, the existing data model---i.e., the last successfully loaded data model---remains intact and is not affected by the failed script. This ensures that the application retains the last known good state of the data, avoiding any partial or inconsistent data loads that could occur due to an error.

When the script encounters an error:

The tables that were successfully loaded prior to the error are retained in the session, but these tables are not merged with the existing data model.

The existing data model before the script was executed remains unchanged and is maintained.

No partial or incomplete data is loaded into the application; hence, the data model remains consistent and reliable.

Qlik Sense Data Architect Reference This behavior is designed to protect the integrity of the data model. In scenarios where script execution fails, the user can debug and fix the script without risking the data integrity of the existing application. The key references include:

Qlik Help Documentation: Provides detailed information on how Qlik Sense handles script errors, highlighting that the existing data model remains unchanged after an error.

Data Load Editor Practices: Best practices dictate ensuring that the script is fully functional before executing it to avoid data inconsistency. In cases where an error occurs, understanding that the current data model is maintained helps in strategic debugging and script correction.