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Qlik Sense Data Architect Certification Exam - 2024 valid practice questions & QSDA2024 exam pdf vce & Qlik Sense Data Architect Certification Exam - 2024 test training simulator
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Qlik QSDA2024 Exam Syllabus Topics:
Topic
Details
Topic 1
- 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.
Topic 2
- 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.
Topic 3
- 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.
Topic 4
- 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.
Topic 5
- 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.
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Qlik Sense Data Architect Certification Exam - 2024 Sample Questions (Q15-Q20):
NEW QUESTION # 15
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:86396169. 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?
- A. FilePath, IF, THEN, Drop
- B. FileExists, FOR EACH, IF
- C. FilePath, FOR EACH, Peek, Drop
- D. FileSize, IF, THEN, END IF
Answer: B
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.
NEW QUESTION # 16
A data architect in the Enterprise Architecture team wants to develop a new application summarizing Qlik Sense usage by all company employees. They also want to gather usage metrics for other systems.
Who should the data architect contact to be granted access to the data?
- A. IT Security Analyst, Qlik Sense Developers, Solutions Architect
- B. IT Security Vice President, Human Resources Analyst, Qlik Sense Developers
- C. IT Security Director, Human Resources Director, Qlik Sense Administrator
- D. IT Security Manager, Qlik Sense Account Manager, Enterprise Architecture Director
Answer: C
Explanation:
When developing an application that summarizes Qlik Sense usage by company employees and also gathers usage metrics for other systems, the data architect needs to ensure they have the correct access to sensitive data. The following roles are crucial:
* IT Security Director:Responsible for the security of IT systems and data. They would ensure that the data architect has the appropriate permissions to access usage metrics and other system data securely.
* Human Resources Director:They manage employee-related data, including employment records that might be necessary for matching employee IDs with usage metrics. This access is crucial for correlating usage data with specific employees.
* Qlik Sense Administrator:This individual has administrative rights over the Qlik Sense environment and can grant access to usage data within Qlik Sense, ensuring that the architect has the necessary data to analyze.
Given the need to securely and correctly handle sensitive data, including employee usage metrics across multiple systems,Option Aincludes all the appropriate contacts for access and permissions.
NEW QUESTION # 17
Refer to the exhibit.
A data architect needs to create a data model for a new app. Users must be able to see:
* Total sales for each customer
* Total sales for a given state
* Customers that have not had any sales
* Names of salesperson and regional account managers
* Total number of sales by date
Which steps should the data architect perform to meet these requirements?
Which steps should the data architect perform to meet these requirements?
- A. 1. Load the Sales table
2. Load the Customers table
3. Load the Employees table twice; name it and alias the EmployeelD field appropriately each time - B. 1. Load the Customers table and alias the CustID field as CustomerlD
2. Use a Mapping Load for the Employees table
3. Load the Sales table and use ApplyMap to get the names for SalesPersonID and RegionalAcctMgrlD - C. 1. Load the Customers table and alias the CustID field as CustomerlD
2. Load the Employees table
3. Load the Sales table and alias the SalesPersonID and RegionalAcctMgrlD fields as EmployeelD - D. 1. Use a Mapping Load for the Employees table
2. Load the Sales table and use ApplyMap to get the names for SalesPersonID and RegionalAcctMgrlD
3. Use a Left Join Load to add the customer details for the Sales table
Answer: A
Explanation:
In the provided scenario, the data architect needs to create a data model that supports various analyses, including total sales for each customer, total sales by state, identifying customers with no sales, and displaying the names of salespersons and regional account managers.
Here's whyOption Cis the correct choice:
* Loading the Sales Table:The Sales table contains key information related to sales transactions, including SaleID, CustomerID, Amount, SaleDate, SalesPersonID, and RegionalAcctMgrID. This table must be loaded first as it will be central to the analysis.
* Loading the Customers Table:The Customers table includes customer details such as CustID, CustName, Address, City, State, and Zip. Loading this table and linking it to the Sales table via the CustomerID field allows you to perform analyses such as total sales per customer and total sales by state. Importantly, loading the customers separately will also allow the identification of customers without any sales.
* Loading the Employees Table Twice:The Employees table must be loaded twice because it is used to look up two different roles in the sales process: the SalesPersonID and the RegionalAcctMgrID. When loading the table twice:
* The first instance of the Employees table will be used to map the SalesPersonID to EmployeeName.
* The second instance will be used to map the RegionalAcctMgrID to EmployeeName.
* Aliasing the EmployeeID field appropriately in each instance is crucial to prevent creating synthetic keys and to ensure the correct association with the roles in the sales process.
This approach ensures that the data model will correctly support all the required analyses, including identifying customers without sales, which is crucial for meeting the business requirements.
* Option AandOption Bpropose using a mapping load and ApplyMap, which can complicate the model and does not directly address all the business requirements.
* Option Dinvolves aliasing fields in a way that could create unnecessary complexity and might not accurately reflect the relationships in the data.
Thus,Option Cis the correct answer as it best meets the requirements while maintaining a clear and functional data model.
NEW QUESTION # 18
Exhibit.
Refer to the exhibit.
A business analyst informs the data architect that not all analysis types over time show the expected data.
Instead they show very little data, if any.
Which Qlik script function should be used to resolve the issue in the data model?
- A. Date(OrderDate) AS OrderDate in both the table "Orders" and "Master Calendar"
- B. TimeStamp#(OrderDate, 'M/D/YYYY hh.mm.ff') AS OrderDate in both the table "Orders" and "Master Calendar"
- C. DatefFloor(OrderDate)) AS OrderDate in both the table "Orders" and "Master Calendar"
- D. TimeStamp(OrderDate) AS OrderDate in both the table "Orders" and "Master Calendar"
Answer: A
Explanation:
In the provided data model, there is an issue where certain types of analysis over time are not showing the expected data. This problem is often caused by a mismatch in the data formats of the OrderDate field between the Orders and MasterCalendar tables.
* Option A:DatefFloor(OrderDate)) would round down to the nearest date boundary, which might not address the root cause if the issue is related to different date and time formats.
* Option B:TimeStamp#(OrderDate, 'M/D/YYYY hh.mm.ff') ensures that the date is interpreted correctly as a timestamp, but this does not resolve potential mismatches in date format directly.
* Option C:TimeStamp(OrderDate) will keep both date and time, which may still cause mismatches if the MasterCalendar is dealing purely with dates.
* Option D:Date(OrderDate) formats the OrderDate to show only the date portion (removing the time part). This function will ensure that the date values are consistent across the Orders and MasterCalendar tables by converting the timestamps to just dates. This is the most straightforward and effective way to ensure consistency in date-based analysis.
In Qlik Sense, dates and timestamps are stored as dual values (both text and numeric), and mismatches can lead to incomplete or incorrect analyses. By using Date(OrderDate) in both the Orders and MasterCalendar tables, you ensure that the analysis will have consistent date values, resolving the issue described.
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 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. Left join Orders and OrderDetails
5. Use Derive statement with the MasterCalendar table and apply the derive fields to 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. Concatenate Orders and OrderDetails
5. Create a link table using the MasterCalendar table and create a concatenated field between OrderDate and ShipmentDate
Answer: A
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
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