Free Practice Questions for Qlik QSDA2024 Exam

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.

When loading data from a QVD file into a Qlik Sense application, if you need to sort the data by a specific field (in this case, the Country field), the Order By clause can be used. However, the Order By clause cannot be directly applied during the initial load from the QVD. Instead, the data should first be loaded into a temporary table and then sorted in a subsequent resident load.

Initial Load from QVD:The data is first loaded into a temporary table (CustTemp) without any sorting.

Resident Load with Order By:After the initial load, you perform a Resident Load from the CustTemp table and apply the Order By clause to sort the data by the Country field in ascending order.

LOAD

Address,

City,

CompanyName,

ContactName,

Country,

_CustomerID,

DivisionID,

DivisionName,

Fax,

Phone,

PostalCode,

StateProvince

RESIDENT CustTemp

ORDER BY Country;

This method ensures that the data is sorted correctly without violating Qlik Sense's loading rules.

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.

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 ReferencesThis 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.

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.

In the provided data model, there is an issue where certain types of analysis over time are not showing the expected data. This problem is often caused by a mismatch in the data formats of the OrderDate field between the Orders and MasterCalendar tables.

Option A:DatefFloor(OrderDate)) would round down to the nearest date boundary, which might not address the root cause if the issue is related to different date and time formats.

Option B:TimeStamp#(OrderDate, 'M/D/YYYY hh.mm.ff') ensures that the date is interpreted correctly as a timestamp, but this does not resolve potential mismatches in date format directly.

Option C:TimeStamp(OrderDate) will keep both date and time, which may still cause mismatches if the MasterCalendar is dealing purely with dates.

Option D:Date(OrderDate) formats the OrderDate to show only the date portion (removing the time part). This function will ensure that the date values are consistent across the Orders and MasterCalendar tables by converting the timestamps to just dates. This is the most straightforward and effective way to ensure consistency in date-based analysis.

In Qlik Sense, dates and timestamps are stored as dual values (both text and numeric), and mismatches can lead to incomplete or incorrect analyses. By using Date(OrderDate) in both the Orders and MasterCalendar tables, you ensure that the analysis will have consistent date values, resolving the issue described.

In this scenario, the data architect needs to load Table_A from an Excel file and ensure that the data is sorted by Field_2. The key here is to correctly load and sort the data in the script.

Understanding the Options:

Option A:

First, it loads the data into a temporary table (Temp) from the Excel file.

Then, it loads the data from the temporary table (Temp) into Table_A, using the ORDER BY Field_2 ASC clause to sort the data by Field_2.

Finally, it drops the temporary table (Temp), leaving the sorted data in Table_A.

Option B:

Directly loads the data from the Excel file into Table_A and applies the ORDER BY Field_2 ASC clause in the same step.

However, the ORDER BY clause in a direct load from an external source like Excel might not work as expected because Qlik Sense does not support ORDER BY when loading directly from a file.

Option C:

Similar to Option A but uses the NoConcatenate keyword to prevent concatenation, which is unnecessary since Temp and Table_A have different names.

While this script works, the NoConcatenate keyword is redundant in this context.

Option D:

The ORDER BY Field_2 ASC is placed before the LOAD statement, which is not a correct usage in Qlik Sense script syntax.

Correct Script Choice:

Option Ais the correct script because it correctly sorts the data after loading it into a temporary table and then loads the sorted data into Table_A. This method ensures that the data is sorted by Field_2 and avoids any issues related to sorting during the initial data load.

References:

Qlik Sense Scripting Best Practices: When sorting data in Qlik Sense, the correct approach is to use a RESIDENT LOAD with an ORDER BY clause after loading the data into a temporary table.

In the scenario presented, a major healthcare organization needs an app that allows users to filter AdmissionDate and DischargeDate by all fields in the Master Calendar table, while also ensuring that users cannot filter on dates that have no associated encounters.

To meet these requirements, the most appropriate approach is to:

Load the Master Calendar twice,once as AdmissionCalendar and once as DischargeCalendar. Each instance should have its fields appropriately aliased to reflect whether they pertain to Admission or Discharge dates.

Load the Encounters tableas usual, but now you have two separate calendar tables that can be linked to the appropriate date fields (AdmissionDate and DischargeDate) in the Encounters table.

This approach ensures:

Users can filter both AdmissionDate and DischargeDateindependently using the fields in their respective calendar tables.

Only relevant datesassociated with actual encounters will be available for filtering, as the calendars are linked specifically to the AdmissionDate and DischargeDate fields.

Efficiency and clarityin the data model, as the fields from the Master Calendar are distinctly assigned to either Admission or Discharge, avoiding any confusion or incorrect filtering.

This method avoids unnecessary complexity and directly meets the healthcare organization's requirements in a straightforward and scalable manner.

In the scenario, two tables (OrderDetails and Customers) are being loaded into the Qlik Sense data model, and these tables are related via the fields CustomerID and CustomerKey. The goal is to ensure that the relationship between these two tables is correctly established in Qlik Sense without creating synthetic keys or data inconsistencies.

Option A:Renaming CustomerKey to CustomerID in the OrderDetails table ensures that the fields will have the same name across both tables, which is necessary to create the relationship. However, renaming is done using AS, which might create an issue if the fields in the original data source have a different meaning.

Option B and C:These options use AUTONUMBER to convert the CustomerKey and CustomerID to unique numeric values. However, using AUTONUMBER for both fields without ensuring they are aligned correctly might lead to incorrect associations since AUTONUMBER generates unique values based on the order of data loading, and these might not match across tables.

Option D:This approach loads the tables with their original field names and then uses the RENAME FIELD statement to align the field names (CustomerKey to CustomerID). This ensures that the key fields are correctly aligned across both tables, maintaining their relationship without introducing synthetic keys or mismatches.