Valid Qlik Latest QSDA2024 Dumps Book Offer You The Best Exam Cram Questions | Qlik Sense Data Architect Certification Exam - 2024
Valid Qlik Latest QSDA2024 Dumps Book Offer You The Best Exam Cram Questions | Qlik Sense Data Architect Certification Exam - 2024
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Qlik Sense Data Architect Certification Exam - 2024 Sample Questions (Q18-Q23):
NEW QUESTION # 18
Refer to the exhibit.
A data architect needs to load data from Customers.qvd and sort the Country field in ascending order. Which method should be used?
- A. Insert an Order By clause after the FROM clause in the CustTemp table
- B. Perform a Resident LOAD of the CustTemp table and insert an Order By clause in this table
- C. Move the Country field to the first position in the field list in the LOAD statement
- D. Insert a Group By clause into the LOAD statement for the CustTemp table after the FROM clause
Answer: B
Explanation:
When loading data from a QVD file into a Qlik Sense application, if you need to sort the data by a specific field (in this case, the Country field), the Order By clause can be used. However, the Order By clause cannot be directly applied during the initial load from the QVD. Instead, the data should first be loaded into a temporary table and then sorted in a subsequent resident load.
* Initial Load from QVD:The data is first loaded into a temporary table (CustTemp) without any sorting.
* Resident Load with Order By:After the initial load, you perform a Resident Load from the CustTemp table and apply the Order By clause to sort the data by the Country field in ascending order.
LOAD
Address,
City,
CompanyName,
ContactName,
Country,
_CustomerID,
DivisionID,
DivisionName,
Fax,
Phone,
PostalCode,
StateProvince
RESIDENT CustTemp
ORDER BY Country;
This method ensures that the data is sorted correctly without violating Qlik Sense's loading rules.
NEW QUESTION # 19
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?
- A. 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 - B. 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 - C. 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 - D. 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
Answer: D
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.
NEW QUESTION # 20
Refer to the exhibits.
On executing a load script of an app, the country field needs to be normalized. The developer uses a mapping table to address the issue. The script runs successfully but the resulting table is not correct.
What should the data architect do?
- A. Use a LEFT JOIN Instead of the APPLYMAP
- B. Review the values of the source mapping table
- C. Create two different mapping tables
- D. Use LOAD DISTINCT on the mapping table
Answer: B
Explanation:
In this scenario, the issue arises from using the applymap() function to normalize the country field values, but the result is incorrect. The reason is most likely related to the values in the source mapping table not matching the values in the Fact_Table properly.
The applymap() function in Qlik Sense is designed to map one field to another using a mapping table. If the source values in the mapping table are inconsistent or incorrect, the applymap() will not function as expected, leading to incorrect results.
Steps to resolve:
* Review the mapping table (MAP_COUNTRY): The country field in the CountryTable contains values such as "U.S.", "US", and "United States" for the same country. To correctly normalize the country names, you need to ensure that all variations of a country's name are consistently mapped to a single value (e.g., "USA").
* Apply Mapping: Review and clean up the mapping table so that all possible variants of a country are correctly mapped to the desired normalized value.
Key References:
* Mapping Tables in Qlik Sense: Mapping tables allow you to substitute field values with mapped values. Any mismatches or variations in source values should be thoroughly reviewed.
* Applymap() Function: This function takes a mapping table and applies it to substitute a field value with its mapped equivalent. If the mapped values are not correct or incomplete, the output will not be as expected.
NEW QUESTION # 21
Exhibit.
One of the data sources a data architect must add for a newly developed app is an Excel spreadsheet. The Region field only has values for the first record for the region. The data architect must perform a transformation so that each row contains the correct Region.
Which function should the data architect implement to resolve this issue?
- A. Above
- B. IntervalMatch
- C. Previous
- D. CrossTable
Answer: C
Explanation:
The given Excel spreadsheet has a Region field where the region value is only specified for the first record within each region. The data architect needs to fill in the missing region values for subsequent rows.
* Previous() Function: The Previous() function in Qlik Sense returns the value of the expression from the previous row. In this case, it can be used to fill down the Region values so that each row contains the correct region information.
* Implementation: The script can be designed to check if the current row's Region value is missing (null). If it is missing, the script can assign the value from the previous row using the Previous() function.
LOAD
If(IsNull(Region), Previous(Region), Region) AS Region,
This logic fills in the missing Region values with the value from the preceding row, which effectively resolves the issue shown in the spreadsheet.
NEW QUESTION # 22
A data architect receives an error while running script.
What will happen to the existing data model?
- A. Newly loaded tables will be merged with the existing data model until the error is resolved.
- B. The latest error-free data model will be maintained.
- C. The data model will be replaced with the tables that were successfully loaded before the error.
- D. The data model will be removed from the application.
Answer: B
Explanation:
In Qlik Sense, when a data load script is executed and an error occurs, the script execution is halted immediately, and any tables that were being loaded at the time of the error are discarded. However, the existing data model-i.e., the last successfully loaded data model-remains intact and is not affected by the failed script. This ensures that the application retains the last known good state of the data, avoiding any partial or inconsistent data loads that could occur due to an error.
When the script encounters an error:
* The tables that were successfully loaded prior to the error are retained in the session, but these tables are not merged with the existing data model.
* The existing data model before the script was executed remains unchanged and is maintained.
* No partial or incomplete data is loaded into the application; hence, the data model remains consistent and reliable.
Qlik Sense Data Architect ReferencesThis behavior is designed to protect the integrity of the data model. In scenarios where script execution fails, the user can debug and fix the script without risking the data integrity of the existing application. The key references include:
* Qlik Help Documentation: Provides detailed information on how Qlik Sense handles script errors, highlighting that the existing data model remains unchanged after an error.
* Data Load Editor Practices: Best practices dictate ensuring that the script is fully functional before executing it to avoid data inconsistency. In cases where an error occurs, understanding that the current data model is maintained helps in strategic debugging and script correction.
NEW QUESTION # 23
......
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