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Free QSDA2022 Exam Braindumps (page: 8)

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PDF with 77 Questions

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?

  1. Save the script for the number interpretation variables in a text file and use the CALL function to insert the variables.
  2. Create an Excel file with the number interpretation variables and use a FOR Next loop to load the variables into Qlik Sense
  3. Save the script for the number interpretation variables in a text file and INLUDE function to insert the variables
  4. Create an Excel file with the number interpretation variables and apply the variables to the app using a mapping table

Answer(s): C

Explanation:

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 global retailer has a large database in which millions of sales transactions are added per hour. Each regional sales manager should only see details for customers in their region. After filtering based on criteria such as region, gender, and income level, sales managers should be able to see the most current detailed transactions.
What should a data architect do to meet these requirements?

  1. Create an app for each sales manager with Qlik GeoAnalytics
  2. Use section access and include a service account in the table
  3. Use On-Demand App Generation (ODAG) and section access
  4. Use section access to restrict sales manager access by region

Answer(s): D

Explanation:



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?









Answer(s): C

Explanation:





Refer to the exhibits.
The first table shows the source table (Original table). This data represents the stocks stored every month for each product:
· The relevant fields are productid, qty, and date.
· The date field represents the calendar months using · The qty field shows the product stock fluctuation from the current month versus the previous month. If there is no fluctuation between months, there are no new entries in the table. The second table shows a Pivot table visualization the data analyst needs to create in the app displaying per each product the monthly trend of available stock. For performance reasons, the data analyst requests the data architect to calculate the running stock quantity of each product for every month in the script.
Which approach should the data architect use?


  1. 1 Generate a Cartesian JOIN between productid and date in a Combined table 2 RIGHT JOIN the Combined table with the Original table to populate the missing qty values
    3. Use PREVIOUS() and RANGESUMQ functions to create the running quantity totals for each product for every month

  2. 1. Generate a Cartesian JOIN between productid and date in a Combined table
    2. LEFT JOIN the Combined table with the Original table to populate the missing qty values
    3. Use PREVIOUSO and SUM() functions to create the running quantity totals for each product for every month

  3. 1. Generate a Calendar table with all dates between the minimum and maximum date values in an Original table
    2. RIGHT JOIN the Calendar table back to the Original table to populate the missing qty values
    3. Use PEEK() and RANGECOUNTO functions to create the running quantity totals for each product for every month

  4. 1 Generate a Calendar table with all dates between the minimum and maximum date values in an Original table
    2. LEFT JOIN the Calendar table back to the Original table to populate the missing qty values

Answer(s): D

Explanation:






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