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

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.

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.

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.