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A data architect wants to combine data on present and historic sales performance. The historic data is stored in a de-normalized archive, and the present data is maintained in a database. The output must be contained in a single table.
Which script should the data architect use?
A data architect completes development of a new app with two data sources Both data sources will also be used by other apps in the future The sources have different data refresh frequencies
• Source 1 Contains frequently updated data and must be refreshed hourly
• Source 2 Contains data that is transferred from a partner and must be refreshed weekly
Tasks must be created to load the data sources and make sure that the new app uses the most current data The data will be stored in two QVDs Which tasks should be created to meet these requirements'?
This option ensures that the data in the two data sources is always up-to-date by scheduling the data refresh tasks to run at the appropriate frequencies. Task 1 runs hourly to refresh data from Source 1, and Task 2 is dependent on Task 1 so that it runs only after Task 1 is completed. This ensures that the data from Source 2 is loaded only after the most current data from Source 1 is loaded.
A data architect plans to build an app that contains geographically diverse data that must be specific to user run-time selections. The source contains transactional data. The app must have minimal impact on already limited server resources.
Which approach should the data architect use?
Using QVDs is the best approach for this scenario, as it allows the data to be stored in a highly compressed format, which will have minimal impact on server resources. Additionally, QVDs can be loaded quickly, which allows for faster access to the data based on user run-time selections. The other options, Loop and Reduce, In-memory, and ODAG, are not valid strategies for this scenario.
A data architect needs to develop multiple apps for various departments. More departments are requesting apps over time The company uses specific requirements for the number interpretation variables (e.g., ThousandSep, DecimalSep) found at the beginning of a LOAD script.
The data architect wants to reduce duplicate scripts but does not want to copy and paste the number interpretation variables each time new app is created. The data architect prefers to use the least amount of script in Qlik Sense.
How should the data architect meet these requirements?
This method involves saving the script for the number interpretation variables in a separate text file, and then using the INCLUDE function to insert the variables into each new app script that is created. This reduces the need to copy and paste the number interpretation variables each time a new app is created and allows the data architect to use the least amount of script in Qlik Sense.
The INCLUDE function is a script statement that allows you to insert the contents of one script file into another script file. This can be used to insert common scripts, such as the number interpretation variables, into multiple app scripts.
A data architect needs to add the UnitCost field from the ProductCost table in the Dim_Products Table.
Which script code should the data architect use?