2025 QSDA2024: Qlik Sense Data Architect Certification Exam - 2024–Efficient Valid Exam Testking

Blog Article

Tags: Valid QSDA2024 Exam Testking, Latest QSDA2024 Test Cram, Valid QSDA2024 Test Answers, Top QSDA2024 Exam Dumps, Exam QSDA2024 Quiz

In this highly competitive IT world, QSDA2024 certification exam are more important than any time before. If you choose Test4Sure, we guarantee that you will easily pass QSDA2024 exam at one time. If you can't pass QSDA2024 Certification Exam, or there are any problems of QSDA2024 exam dumps, we will give a full refund unconditionally. What are you waiting for? Hurry up and fight for your IT dream.

Qlik QSDA2024 Exam Syllabus Topics:

Topic	Details
Topic 1	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 2	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.
Topic 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.
Topic 4	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 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.

>> Valid QSDA2024 Exam Testking <<

Latest QSDA2024 Test Cram - Valid QSDA2024 Test Answers

Our QSDA2024 test braindumps are carefully developed by experts in various fields, and the quality is trustworthy. What's more, after you purchase our products, we will update our QSDA2024 exam questions according to the new changes and then send them to you in time to ensure the comprehensiveness of learning materials. We also have data to prove that 99% of those who use our QSDA2024 Latest Exam torrent to prepare for the exam can successfully pass the exam and get QSDA2024 certification. As long as you decide to choose our QSDA2024 exam questions, you will have an opportunity to prove your abilities, so you can own more opportunities to embrace a better life.

Qlik Sense Data Architect Certification Exam - 2024 Sample Questions (Q46-Q51):

NEW QUESTION # 46
Exhibit.

Refer to the exhibit.
A data architect is loading the tables and a synthetic key is generated.
How should the data architect resolve the synthetic key?

A. Remove the LineNo field from Shipments and use the AutoNumber function on the OrderlD field
B. Create a composite key using OrderlD and UneNo
C. Create a composite key using OrderlD and LineNo, and remove OrderlD and LineNo from Shipments
D. Remove the LineNo field from both tables and use the AutoNumber function on the OrderlD field

Answer: B

Explanation:
In this scenario, the data architect is loading two tables, Orders and Shipments, into Qlik Sense, and a synthetic key is being generated due to the presence of shared fields (OrderID and LineNo) between these tables.
Understanding the Issue:
* Synthetic Keys: Qlik Sense automatically creates synthetic keys when two or more tables share multiple fields with the same names. While synthetic keys aren't necessarily problematic, they can sometimes lead to incorrect or unexpected data associations and should be resolved when possible to maintain clarity and control over the data model.
* The tables Orders and Shipments share the fields OrderID and LineNo. In this context, these fields together uniquely identify each record, so they are both necessary for accurate data linkage.
Correct Resolution Approach:
Option C: Create a composite key using OrderID and LineNois the best approach.
Here's why:
* Composite Key Creation:
* By creating a composite key that combines OrderID and LineNo (e.g., OrderID & '-' & LineNo), you ensure that each line in the orders and shipments tables is uniquely identified. This composite key will accurately link the related records from the Orders and Shipments tables.
* Avoiding Synthetic Keys:
* By manually creating this composite key, you eliminate the need for Qlik Sense to generate a synthetic key, thereby simplifying the data model and ensuring that data associations are clear and controlled.
* Retaining Both Fields:
* This approach allows you to keep both OrderID and LineNo as separate fields in your tables if needed for other analyses or reporting purposes, while using the composite key for linking the tables.
References:
* Qlik Sense Data Modeling Best Practices: When dealing with multiple fields that are used together to uniquely identify records, it is recommended to create composite keys rather than relying on Qlik Sense's synthetic keys for clarity and better control.

NEW QUESTION # 47
Exhibit.

Refer to the exhibits.
The Orders table contains a list of orders and associated details. A data architect needs to replace the SupplierlD with the SupplierName using the second table as the source.
The output must be a single table.
Which script should the data architect use?

Answer: C

Explanation:
In this scenario, the data architect needs to replace the SupplierID in the Orders table with the corresponding SupplierName from the Suppliers table, and the desired output should be a single table that includes all the order details along with the SupplierName instead of the SupplierID.
Analyzing the Options:
* Option A:
* Uses a MAPPING LOAD followed by an APPLYMAP to replace SupplierID with SupplierName in the Orders table. However, the table is dropped afterward, which means it won't produce the required output.
* The MAPPING LOAD approach is generally used to map values but is not necessary in this context as we are combining data from two tables directly.
* Option B:
* This option attempts to LEFT JOIN the Products table with the Suppliers table, but it does not directly address replacing SupplierID with SupplierName in the Orders table.
* Additionally, it does not remove the SupplierID after the join, which is essential for the correct output.
* Option C:
* This option uses a LEFT JOIN with the DISTINCT keyword on the SupplierID field to avoid duplicates. The SupplierName is correctly joined to the Orders table, replacing the SupplierID.
* This approach is the most appropriate because it results in a single table containing all order details with the SupplierName instead of the SupplierID.
* Option D:
* Similar to Option A, but it also introduces an unnecessary renaming step with MAPPING LOAD.
It's redundant and does not improve the solution over Option C.
Correct Script Choice:
Option Cis the correct script because:
* It ensures that SupplierName replaces SupplierID in the Orders table using a LEFT JOIN.
* The DISTINCT keyword is applied to the SupplierID field to prevent duplicate rows during the join.
* The result is a single table containing the required information with SupplierName in place of SupplierID.
References:
* Qlik Sense Join Operations: Using the correct JOIN type and ensuring proper deduplication (with DISTINCT if necessary) is key to merging tables in Qlik Sense.

NEW QUESTION # 48

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. Review the values of the source mapping table
B. Use a LEFT JOIN Instead of the APPLYMAP
C. Use LOAD DISTINCT on the mapping table
D. Create two different mapping tables

Answer: A

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 # 49
Exhibit.

Refer to the exhibit.
A data architect wants to transform the input data set to the output data set. Which prefix to the Qlik Sense LOAD command should the data architect use?

A. Hierarchy Be longsTo
B. Peek
C. Generic
D. PivotTable

Answer: C

Explanation:
In this scenario, the data architect wants to transform the input dataset, which is in a key-value pair structure, into a table where each attribute becomes a column with its corresponding value under the relevant key.
Understanding the Requirement:
* Theinputdata consists of three fields: Key, Attribute, and Value.
* The desiredoutputstructure has the Key as a primary identifier, and the Attributes (like Color, Diameter, Height, etc.) are spread across the columns, with corresponding values filled in each row.
Best Method to Achieve this Transformation:
* The appropriate method to convert key-value pairs into a structured table where each unique attribute becomes a separate column is theGeneric Loadfunction in Qlik Sense.
Why Generic?
* Generic Loadis specifically designed for situations where data is stored in a key-value format (like the one provided) and needs to be converted into a more traditional tabular format, with attributes as columns.
* It creates a separate table for each combination of Key and Attribute, effectively "pivoting" the attribute values into columns in the output table.
How it Works:
* When applying a GENERIC LOAD to the input dataset, Qlik Sense will generate multiple tables, one for each Attribute. However, in the final data model, Qlik Sense automatically joins these tables by the Key field, effectively producing the desired output structure.
References:
* Qlik Sense Documentation on Generic Load: The documentation outlines how to use the Generic Load to handle key-value pairs and pivot them into a more traditional table format.

NEW QUESTION # 50
Exhibit.

A large electronics company re-assigns sales people once per year from one Department to another.
SPID is the Salesperson ID; the SPID for each individual sales person Name remains constant. The Department for a SPID may change; each change is stored in the Dynamic Dimension data.
Four tables need to be linked correctly: a transaction table, a dynamic salesperson dimension, a static salesperson dimension, and a department dimension.
Which script prefix should the data architect use?

A. Partial Reload
B. Merge
C. Semantic
D. IntervalMatch

Answer: D

Explanation:
In the scenario described, the Dynamic Dimension data tracks changes in department assignments for salespeople over time. To correctly link the transaction data with the salesperson data and ensure that sales are associated with the correct department based on the date, an IntervalMatch function should be used.
IntervalMatchis designed to match discrete data (like transaction dates) with a range of dates. In this case, each salesperson's department assignment is valid over a period of time, and the IntervalMatch function can be used to link the transaction data with the correct department for each salesperson based on the transaction date.
* Option A (Merge):This option is incorrect as it refers to combining data sets, which doesn't address the need to handle the dynamic, date-based department assignments.
* Option B (IntervalMatch):This is the correct choice because it allows you to match each transaction with the correct department assignment based on the ChangeDate in the Dynamic Dimension data.
* Option C (Partial Reload):This refers to reloading only part of the data, which is not relevant to linking tables based on date ranges.
* Option D (Semantic):This option is not applicable as it refers to a broader approach to data modeling and interpretation rather than specifically linking data based on time intervals.
Thus,IntervalMatchis the correct method for linking the transaction data with the dynamic salesperson dimension, ensuring that each transaction is associated with the correct department based on the historical assignment data.

NEW QUESTION # 51
......

Never have we made our customers disappointed about our QSDA2024 study guide. So we have enjoyed good reputation in the market for about ten years. In the future, we will stay integrity and research more useful QSDA2024 learning materials for our customers. Please continue supporting our QSDA2024 Exam Questions and we will make a better job with your warm encourages and suggestions. So if you have any opinions about our QSDA2024 learning quiz, just leave them for us.

Latest QSDA2024 Test Cram: https://www.test4sure.com/QSDA2024-pass4sure-vce.html

Report this page

2025 QSDA2024: QLIK SENSE DATA ARCHITECT CERTIFICATION EXAM - 2024–EFFICIENT VALID EXAM TESTKING

2025 QSDA2024: Qlik Sense Data Architect Certification Exam - 2024–Efficient Valid Exam Testking