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Free QSDA2024 Exam Braindumps (page: 4)

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PDF with 50 Questions

A data architect wants reflect a value of the variable in the script log for tracking purposes. The variable is defined as:



Which statement should be used to track the variable's value?

A)



B)



C)



D)

  1. Option A
  2. Option B
  3. Option C
  4. Option D

Answer(s): B

Explanation:

In Qlik Sense, the TRACE statement is used to print custom messages to the script execution log. To output the value of a variable, particularly one that is dynamically assigned, the correct syntax must be used to ensure that the variable's value is evaluated and displayed correctly.


The variable vMaxDate is defined with the LET statement, which means it is evaluated immediately, and its value is stored.

When using the TRACE statement, to output the value of vMaxDate, you need to ensure the variable's value is expanded before being printed. This is done using the $() expansion syntax.

The correct syntax is TRACE #### $(vMaxDate) ####; which evaluates the variable vMaxDate and inserts its value into the log output.

Key Qlik Sense Data Architect


Reference:

Variable Expansion: In Qlik Sense scripting, $(variable_name) is used to expand and insert the value of the variable into expressions or statements. This is crucial when you want to output or use the value stored in a variable.

TRACE Statement: The TRACE command is used to write messages to the script log. It is commonly used for debugging purposes to track the flow of script execution or to verify the values of variables during script execution.



Exhibit.



Refer to the exhibit.

A data architect is working on a Qlik Sense app the business has created to analyze the company orders and shipments.

To understand the table structure, the business has given the following summary:

· Every order creates a unique orderlD and an order date in the Orders table

· An order can contain one or more order lines one for each product ID in the order details table

· Products In the order are shipped (shipment date) as soon as they are ready and can be shipped separately

· The dates need to be analyzed separately by Year, Month, and Quarter

The data architect realizes the data model has issues that must be fixed.
Which steps should the data architect perform?

  1. 1. Create a key with OrderlD and ProductID in the OrderDetails table and in the Shipments table
    2. Delete the ShipmentID in the Orders table
    3. Delete the ProductID and OrderlD in the Shipments table
    4. Left join Orders and OrderDetails
    5. Use Derive statement with the MasterCalendar table and apply the derive fields to OrderDate and ShipmentDate
  2. 1. Create a key with OrderlD and ProductID In the OrderDetails table and in the Orders table
    2. Delete the ShipmentID in the Shipments table
    3. Delete the ProductID and OrderlD in the OrderDetails table
    4. Concatenate Orders and OrderDetails
    5. Create a link table using the MasterCalendar table and create a concatenated field between OrderDate and ShipmentDate
  3. 1. Create a key with OrderlD and ProductID in the OrderDetails table and in the Shipments table
    2. Delete the ShipmentID in the Orders table
    3. Delete the ProductID and OrderlD In the Shipments table
    4. Concatenate Orders and OrderDetails
    5. Create a link table using the MasterCalendar table and create a concatenated field between OrderDate and ShipmentDate
  4. 1. Create a key with OrderlD and ProductID in the OrderDetails table and in the Orders table
    2. Delete the ShipmentID in the Shipments table
    3. Delete the ProductID and OrderlD in the OrderDetails table
    4. Left join Orders and OrderDetails

    5. Use Derive statement with the MasterCalendar table and apply the derive fields to OrderDate and ShipmentDate

Answer(s): C

Explanation:

In the given data model, there are several issues related to table relationships and key fields that need to be addressed to create a functional and optimized data model. Here's how each step in the chosen solution (Option C) resolves these issues:

Create a key with OrderID and ProductID in the OrderDetails table and in the Shipments table:

By creating a composite key with OrderID and ProductID, you uniquely identify each line item in both the OrderDetails and Shipments tables. This step is crucial for ensuring that each product within an order is correctly associated with its respective shipment.

Delete the ShipmentID in the Orders table:

The ShipmentID in the Orders table is redundant because the Shipments table already captures this information at a more granular level (i.e., at the product level). Removing ShipmentID avoids potential circular references or synthetic keys.

Delete the ProductID and OrderID in the Shipments table:

After creating the composite key in step 1, the individual ProductID and OrderID fields in the Shipments table are no longer necessary for joins. Removing them reduces redundancy and simplifies the table structure.

Concatenate Orders and OrderDetails:

Concatenating Orders and OrderDetails into a single table creates a unified table that contains all necessary order-related information. This helps in simplifying the model and avoiding issues related to managing separate but related tables.

Create a link table using the MasterCalendar table and create a concatenated field between OrderDate and ShipmentDate:

A link table is created to associate the combined table with the MasterCalendar. By creating a concatenated field that combines OrderDate and ShipmentDate, you ensure that both dates are properly linked to the calendar, allowing for accurate time-based analysis.



A data architect needs to upload data from ten different sources, but only if there are any changes after the last reload.
When data is updated, a new file is placed into a folder mapped to
E:\486396169. The data connection points to this folder.

The data architect plans a script which will:

1. Verify that the file exists

2. If the file exists, upload it Otherwise, skip to the next piece of code.

The script will repeat this subroutine for each source.
When the script ends, all uploaded files will be removed with a batch procedure.
Which option should the data architect use to meet these requirements?

  1. FilePath, FOR EACH, Peek, Drop
  2. FileSize, IF, THEN, END IF
  3. FilePath, IF, THEN, Drop
  4. FileExists, FOR EACH, IF

Answer(s): D

Explanation:

In this scenario, the data architect needs to verify the existence of files before attempting to load them and then proceed accordingly. The correct approach involves using the FileExists() function to check for the presence of each file. If the file exists, the script should execute the file loading routine. The FOR EACH loop will handle multiple files, and the IF statement will control the conditional loading.

FileExists(): This function checks whether a specific file exists at the specified path. If the file exists, it returns TRUE, allowing the script to proceed with loading the file.

FOR EACH: This loop iterates over a list of items (in this case, file paths) and executes the enclosed code for each item.

IF: This statement checks the condition returned by FileExists(). If TRUE, it executes the code block for loading the file; otherwise, it skips to the next iteration.

This combination ensures that the script loads data only if the files are present, optimizing the data loading process and preventing unnecessary errors.



The data architect has been tasked with building a sales reporting application.

· Part way through the year, the company realigned the sales territories

· Sales reps need to track both their overall performance, and their performance in their current territory

· Regional managers need to track performance for their region based on the date of the sale transaction

· There is a data table from HR that contains the Sales Rep ID, the manager, the region, and the start and end dates for that assignment

· Sales transactions have the salesperson in them, but not the manager or region.

What is the first step the data architect should take to build this data model to accurately reflect performance?

  1. Implement an "as of calendar against the sales table and use ApplyMap to fill in the needed management data
  2. Create a link table with a compound key of Sales Rep / Transaction Date to find the correct manager and region
  3. Use the IntervalMatch function with the transaction date and the HR table to generate point in time data
  4. Build a star schema around the sales table, and use the Hierarchy function to join the HR data to the model

Answer(s): C

Explanation:

In the provided scenario, the sales territories were realigned during the year, and it is necessary to track performance based on the date of the sale and the salesperson's assignment during that period. The IntervalMatch function is the best approach to create a time-based relationship between the sales transactions and the sales territory assignments.

IntervalMatch: This function is used to match discrete values (e.g., transaction dates) with intervals (e.g., start and end dates for sales territory assignments). By matching the transaction dates with the intervals in the HR table, you can accurately determine which territory and manager were in effect at the time of each sale.

Using IntervalMatch, you can generate point-in-time data that accurately reflects the dynamic nature of sales territory assignments, allowing both sales reps and regional managers to track performance over time.






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