Pass the Qlik Sense Data Architect QSDA2024 Questions and answers with ValidTests

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.

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 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.

In the scenario where the data model is built with a composite key (keyYearMonthCustNo) to resolve synthetic keys, the following outcomes occur:

Sales and Budget Data Integration:

The composite key ensures that each combination of Year, Month, and Customer is uniquely represented in the combined Sales and Budget data.

During data selection (e.g., when a specific month is selected), Qlik Sense will show all the customer names that have either Sales or Budget data associated with that month.

Resulting Data View:

For the selected month, customers with sales records will display their Sales data. However, if the corresponding Budget data is missing, the Budget column will contain null values.

Similarly, if a customer has a Budget but no Sales data for the selected month, the Sales column will show null values.

Validation Outcome:When the data architect selects a month, they will see the following:

Customer Names and Sales recordsfor the selected month, where the Sales column will have values and the Budget column may contain null or non-null values depending on the data availability.

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.