QSDA2024 Exam Dumps : Qlik Sense Data Architect Certification Exam – 2024

The scenario describes an app that is experiencing long load times due to the need to pull all records, both new and historical, from three large databases. This situation puts a strain on both the Qlik environment and the source databases. Given that all data is required for analysis, a full reload each time can be inefficient and resource-intensive.

Implementingincremental loadis a widely recommended approach in such cases. Incremental loading allows you to load only new or changed data since the last reload, rather than reloading all the data every time. This significantly reduces the time and resources required for reloading, as only a subset of the data needs to be processed during each reload. QVD (QlikView Data) files are typically used to store the historical data, while only the new or updated records are fetched from the source databases.

This approach would help:

Reduce the load on the source databases.

Shorten the data reload window.

Maintain historical data efficiently while ensuring that all new data is captured.

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 provided scenario, the goal is to export tables from a Qlik Sense model based on rules specified in an external text file. The structure of the text file indicates which table to export, the filename to use, and how many copies to create.

Given this structure, the data architect needs to:

Loop through each row in the text file to process each table.

Use an IF statement to check whether the specified table exists in the model (though it's mentioned they are verified to exist, this step may involve conditional logic to ensure the rules are correctly followed).

Use another IF statement to handle the creation of multiple copies, ensuring each file is named incrementally (e.g., Clients1.qvd, Clients2.qvd, etc.).

Key Script Strategies:

Loop: A loop is necessary to iterate through each row of the text file to process the tables specified for export.

IF Statements: The first IF statement checks conditions such as whether the table should be exported (based on additional logic if needed). The second IF statement handles the creation of multiple copies by incrementing the filename.

This approach covers all the necessary logic with the minimum set of scripting strategies, ensuring that each table is exported according to the rules defined.