QlikView QSDA2024 Dumps PDF Free Download - Page: 10

QUESTION: 6

A data architect executes the following script:

Which values does the OrderDate field contain after executing the script?

20210131, 2020/01/31, 31/01/2019
20210131, 2020/01/31, 31/01/2019, 9999
20210131, 2020/01/31, 31/01/2019, 0
20210131, 2020/01/31, 31/01/2019, 31/12/2022

Answer(s): D

Explanation:

In the script provided, the alt() function is used to handle various date formats. The alt() function in Qlik Sense evaluates a list of expressions and returns the first valid expression. If none of the expressions are valid, it returns the last argument provided (in this case, '31/12/2022').

Step-by-step breakdown:

The alt() function checks the Date field for three different formats:

YYYYMMDD

YYYY/MM/DD

DD/MM/YYYY

If none of these formats match the value in the Date field, the default date '31/12/2022' is assigned.

Values in the Date field:

20210131: Matches the first format YYYYMMDD.

2020/01/31: Matches the second format YYYY/MM/DD.

31/01/2019: Matches the third format DD/MM/YYYY.

9999: Does not match any of the formats, so the alt() function returns the default value '31/12/2022'.

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QUESTION: 7

A data architect needs to load large amounts of data from a database that is continuously updated.

· New records are added, and existing records get updated and deleted.

· Each record has a LastModified field.

· All existing records are exported into a QVD file.

· The data architect wants to load the records into Qlik Sense efficiently.

Which steps should the data architect take to meet these requirements?

1. Load the existing data from the QVD.
2. Load the new and updated data from the database without the rows that have just been loaded from the QVD and concatenate with data from the QVD.
3. Load all records from the key field from the database and use an INNER JOIN on the previous table.
1. Use a partial LOAD to load new and updated data from the database.
2. Load the existing data from the QVD without the updated rows that have just been loaded from the database and concatenate with the new and updated records.
3. Use the PEEK function to remove the deleted rows.
1. Load the new and updated data from the database.
2. Load the existing data from the QVD without the updated rows that have just been loaded from the database and concatenate with the new and updated records.
3. Load all records from the key field from the database and use an INNER JOIN on the previous table.
1. Load the existing data from the QV
2. Load new and updated data from the database. Concatenate with the table loaded from the QV
3. Create a separate table for the deleted rows and use a WHERE NOT EXISTS to remove these records.

Answer(s): D

Explanation:

When dealing with a database that is continuously updated with new records, updates, and deletions, an efficient data load strategy is necessary to minimize the load time and keep the Qlik Sense data model up-to-date.

Explanation of Steps:

Load the existing data from the QVD:

This step retrieves the already loaded and processed data from a previous session. It acts as a base to which new or updated records will be added.

Load new and updated data from the database. Concatenate with the table loaded from the QVD:

The next step is to load only the new and updated records from the database. This minimizes the amount of data being loaded and focuses on just the changes.

The new and updated records are then concatenated with the existing data from the QVD, creating a combined dataset that includes all relevant information.

Create a separate table for the deleted rows and use a WHERE NOT EXISTS to remove these records:

A separate table is created to handle deletions. The WHERE NOT EXISTS clause is used to identify and remove records from the combined dataset that have been deleted in the source database.

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QUESTION: 8

Exhibit.

Refer to the exhibit.

The data architect needs to build a model that contains Sales and Budget data for each customer. Some customers have Sales without a Budget, and other customers have a Budget with no Sales.

During loading, the data architect resolves a synthetic key by creating the composite key.

For validation, the data architect creates a table that contains Customer, Month, Sales, and Budget columns.

What will the data architect see when selecting a month?

Customer Names and Sales records for the selected month, Budgets column can contain null or non-null values
All Customer Names for both Sales and Budget records for the selected month
Customer Names and Sales records for the selected month but with only non-null values in Budget column
Customer Names and Budaets records for the selected month. Sales column can contain null or non-null values

Answer(s): A

Explanation:

In the scenario where the data model is built with a composite key (keyYearMonthCustNo) to resolve synthetic keys, the following outcomes occur:

Sales and Budget Data Integration:

The composite key ensures that each combination of Year, Month, and Customer is uniquely represented in the combined Sales and Budget data.

During data selection (e.g., when a specific month is selected), Qlik Sense will show all the customer names that have either Sales or Budget data associated with that month.

Resulting Data View:

For the selected month, customers with sales records will display their Sales data. However, if the corresponding Budget data is missing, the Budget column will contain null values.

Similarly, if a customer has a Budget but no Sales data for the selected month, the Sales column will show null values.

Validation Outcome:
When the data architect selects a month, they will see the following:

Customer Names and Sales records for the selected month, where the Sales column will have values and the Budget column may contain null or non-null values depending on the data availability.

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QUESTION: 9

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)

Option A
Option B
Option C
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.

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QUESTION: 10

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. 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
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
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
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.

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QlikView Qlik Sense Data Architect Certification - 2024 QSDA2024 Dumps in PDF

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