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Qlik QSDA2024 考試大綱：

主題
簡介

主題 1

• Identify Requirements: This section assesses the abilities of data analysts in defining key business requirements. It includes tasks such as identifying stakeholders, selecting relevant metrics, and determining the level of granularity and aggregation needed.

主題 2

• Data Model Design: In this section, data analysts and data architects are tested on their ability to determine relevant measures and attributes from each data source.

主題 3

• Data Connectivity: This part evaluates how data analysts identify necessary data sources and connectors. It focuses on selecting the most appropriate methods for establishing connections to various data sources.

主題 4

• Data Transformations: This section examines the skills of data analysts and data architects in creating data content based on specific requirements. It also covers handling null and blank data and documenting Data Load scripts.

主題 5

• Validation: This section tests data analysts and data architects on how to validate and test scripts and data. It focuses on selecting the best methods for ensuring data accuracy and integrity in given scenarios.

 

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最新的 Qlik Certification QSDA2024 免費考試真題 (Q24-Q29):

問題 #24
Refer to the exhibit.

A data architect needs to build a dashboard that displays the aggregated sates for each sales representative. All aggregations on the data must be performed in the script.
Which script should the data architect use to meet these requirements?

• A.
• B.
• C.
• D.

答案：D

解題說明：
The goal is to display the aggregated sales for each sales representative, with all aggregations being performed in the script. Option C is the correct choice because it performs the aggregation correctly using a Group by clause, ensuring that the sum of sales for each employee is calculated within the script.
* Data Load:
* The Data table is loaded first from the Sales table. This includes the OrderID, OrderDate, CustomerID, EmployeeID, and Sales.
* Next, the Emp table is loaded containing EmployeeID and EmployeeName.
* Joining Data:
* A Left Join is performed between the Data table and the Emp table on EmployeeID, enriching the data with EmployeeName.
* Aggregation:
* The Summary table is created by loading the EmployeeName and calculating the total sales using the sum([Sales]) function.
* The Resident keyword indicates that the data is pulled from the existing tables in memory, specifically the Data table.
* The Group by clause ensures that the aggregation is performed correctly for each EmployeeName, summarizing the total sales for each employee.
Key Qlik Sense Data Architect References:
* Resident Load: This is a method to reuse data that is already loaded into the app's memory. By using a Resident load, you can create new tables or perform calculations like aggregation on the existing data.
* Group by Clause: The Group by clause is essential when performing aggregations in the script. It groups the data by specified fields and performs the desired aggregation function (e.g., sum, count).
* Left Join: Used to combine data from two tables. In this case, Left Join is used to enrich the sales data with employee names, ensuring that the sales data is associated correctly with the respective employee.
Conclusion:Option C is the most appropriate script for this task because it correctly performs the necessary joins and aggregations in the script. This ensures that the dashboard will display the correct aggregated sales per employee, meeting the data architect's requirements.

 

問題 #25
A data architect needs to acquire social media data for the past 10 years. The data architect needs to track all changes made to the source data, include all relevant fields, and reload the application four times a day.
What information does the data architect need?

• A. A field with ModificationTime, a primary key field to sort out updated records, insert and append records, update records
• B. A field with ModificationTime, a primary key field to sort out updated records, insert and update records, remove records
• C. A field with record creation time, a secondary key field to remove deleted records, configure reload task to load four times a day
• D. A field with social media source, a set of key fields to sort out updated records, configure reload task to load four times a day

答案：B

解題說明：
The scenario describes a need to track social media data over the past 10 years, capturing all changes (inserts, updates, deletes) while reloading the data four times a day.
To manage this:
* ModificationTime: This field is essential for tracking changes over time. It indicates when a record was last modified, allowing the script to determine whether it needs to insert, update, or delete records.
* Primary Key Field: A primary key is crucial for uniquely identifying records. It enables the script to match records in the source with those already loaded, facilitating updates and deletions.
* Insert and Update Records: The script should handle both inserting new records and updating existing ones based on the ModificationTime.
* Remove Records: If records are deleted in the source, they should also be removed in the Qlik Sense data model to maintain consistency.
This approach ensures that all changes in the social media data are accurately captured and reflected in the Qlik Sense application.

 

問題 #26
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 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
• 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 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

答案：A

解題說明：
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.

 

問題 #27

Refer to the exhibit.
What does the expression sum< [orderMetAmount ]) return when all values in LineNo are selected?

• A. 0
• B. 1
• C. 2
• D. 3

答案：C

解題說明：
The expression sum([OrderNetAmount]) sums the values in the OrderNetAmount field across the dataset.
Given that the dataset includes an inline table that is joined with another, the expression calculates the sum of OrderNetAmount for all selected rows. In this scenario, all values in LineNo are selected, which doesn't affect the summation of OrderNetAmount because LineNo isn't directly used in the sum calculation.
Step-by-step Calculation:
* The Orders table contains the OrderNetAmount for each order. The values provided are 90, 500, 100, and 120.
* Adding these values together:90+500+100+120=81090 + 500 + 100 + 120 = 81090+500+100+120=810
* However, after the Left Join operation with the OrderDetails table, some of these rows might be duplicated if the join results in multiple matches. But since the field being summed, OrderNetAmount, is from the original Orders table and not affected by the details in OrderDetails, the sum still remains consistent with the original values in the Orders table.
Thus, the sum of OrderNetAmount is 149014901490, based on the combined effects of the original data structure and the join operation.

 

問題 #28

Refer to the exhibit
A large transport company (Company A) acquires a smaller rival (Company B).
Company A has been using Qlik Sense tor 6 years to track revenue per ship journey. Ship journeys with no revenue (such as journeys to shipyards for repair) always show revenue of $0.
Company A wants to combine its data set with the data set of the acquired Company B. Company B's ship journey data shows $0 revenue in one of the following ways:
* A NULL value
* A value with one or more blank spaces (ASCII char code 32)
The data architect wants to conform the Company B data to the Company A standard, specifically regarding the use of an explicit $0 for journeys without revenue. Which script line should the data architect use?

• A.
• B.
• C.
• D.

答案：C

解題說明：
In this scenario, the data architect needs to conform the revenue data from Company B to match the data standard of Company A, where $0 is explicitly used to represent journeys without revenue.
Explanation of the Correct Script:
* Option A:money(replace(Revenue, chr(32), 0)) AS [Revenue Conformed]
* replace(Revenue, chr(32), 0):This part of the expression replaces any spaces (ASCII character code 32) in the Revenue field with 0.
* money(...):This function formats the resulting value as currency. Since Company B may have either null values or spaces where 0 should be, this script ensures that any blanks are replaced with 0 and then formatted as currency.
Why Option A is Correct:
* Handling Spaces:The replace() function is effective in replacing spaces with 0, conforming to Company A's standard of using $0 for non-revenue journeys.
* Handling NULL Values:The money() function is used to ensure the final output is formatted as currency. However, it's important to note that NULL values are not directly handled by the replace() function, which is why it is applied before money() to deal with spaces.

 

問題 #29
......

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