QSDA2024 Exam Success, QSDA2024 Updated CBT

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The Qlik QSDA2024 desktop practice exam software is customizable and suits the learning needs of candidates. A free demo of the Qlik Sense Data Architect Certification Exam - 2024 (QSDA2024) desktop software is available for sampling purposes. You can change Qlik QSDA2024 Practice Exam's conditions such as duration and the number of questions. This simulator creates a Qlik Sense Data Architect Certification Exam - 2024 (QSDA2024) real exam environment that helps you to get familiar with the original test.

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 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 3	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 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.
Topic 5	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.

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According to personal propensity and various understanding level of exam candidates, we have three versions of QSDA2024 practice materials for your reference. Here are the respective features and detailed disparities of our QSDA2024 practice materials. Pdf version- it is legible to read and remember, and support customers’ printing request, so you can have a print and practice in papers. Software version-It support simulation test system, and times of setup has no restriction. Remember this version support Windows system users only. App online version-Be suitable to all kinds of equipment or digital devices. Be supportive to offline exercise on the condition that you practice it without mobile data.

Qlik Sense Data Architect Certification Exam - 2024 Sample Questions (Q31-Q36):

NEW QUESTION # 31
exhibit.

A data architect is validating that the script section, as shown in the exhibit, is working properly. They need to stop the script with a preview of the value used with the Load statement.
Where should the data architect put the debugger breakpoint?

Answer: B

Explanation:
In this scenario, the data architect needs to validate the script and specifically ensure that the vMaxDate variable is being correctly utilized in the LOAD statement. The goal is to stop the script execution at a point where the variable's value can be previewed.
Understanding the Options:
* Option Aplaces the breakpoint just after the assignment of the variable vMaxDate in the Where clause but before any data is loaded.
* Option B, C, and Drepresent placements of the breakpoint after the LOAD statement begins processing the Resident table, which means that the variable vMaxDate would have already been utilized.
Correct Breakpoint Placement:
* Option Ais the correct choice because placing the breakpoint at this point allows you to preview the value of vMaxDate right before it is used in the Where clause. This placement ensures that the script execution halts before loading the data, allowing you to validate whether vMaxDate is correctly defined and whether it correctly filters the data based on the [Date] field.
* If the breakpoint were placed after the LOAD statement (as in Options B, C, or D), the script would have already attempted to load the data, making it too late to inspect the variable's value before it's used.
References:
* Qlik Sense Debugging Best Practices: When debugging, it is crucial to set breakpoints before the execution of a critical operation where the values of variables or fields are used to ensure that they hold the expected data.

NEW QUESTION # 32
A company generates l GB of ticketing data daily. The data is stored in multiple tables. Business users need to see trends of tickets processed for the past 2 years. Users very rarely access the transaction-level data for a specific date. Only the past 2 years of data must be loaded, which is 720 GB of data.
Which method should a data architect use to meet these requirements?

A. Load only 2 years of data and use best practices in scripting and visualization to calculate and display aggregated data
B. Load only 2 years of data in an aggregated app and create a separate transaction app for occasional use
C. Load only aggregated data for 2 years and use On-Demand App Generation (ODAG) for transaction data
D. Load only aggregated data for 2 years and apply filters on a sheet for transaction data

Answer: C

NEW QUESTION # 33
Exhibit.

Refer to the exhibit.
A major healthcare organization requests a new app with the following requirements:
* Users can filter AdmissionDate and DischargeDate by all fields in the Master Calendar table
* Use an existing QVD file, which includes dates 20 years into the future
* Users should not be able to filter on dates that have no associated encounters Which approach should the data architect take to meet these requirements?

A. 1. Load the Encounters table
2. Perform a Left Join Load on the Encounters table to the master calendar and alias the date fields appropriately for the Admission Date
3. Perform a Left Join Load on the Encounters table to the master calendar and alias the date fields appropriately for the Discharge Date
B. 1. Load the Master Calendar and Encounters tables
2. Perform a Join Load on the Encounters table to the Resident master calendar and alias the date fields appropriately for the Admission Date
3. Perform a Join Load on the Encounters table to the Resident master calendar and alias the date fields appropriately for the Discharge Date
C. 1. Load the master calendar as AdmissionCalendar and alias the fields to reflect they are for Admission
2. Load the master calendar as DischargeCalendar and alias the fields to reflect they are for Discharge
3. Load the Encounters table
D. 1. Load the master calendar
2. Create two mapping tables called AdmissionCalendar and DischargeCalendar from the Resident master calendar thatfeas all fields appropriately named
3. Load the Encounters table and use ApplyMap for the AdmissionDate and DischargeDate appropriately

Answer: C

Explanation:
In the scenario presented, a major healthcare organization needs an app that allows users to filter AdmissionDate and DischargeDate by all fields in the Master Calendar table, while also ensuring that users cannot filter on dates that have no associated encounters.
To meet these requirements, the most appropriate approach is to:
* Load the Master Calendar twice,once as AdmissionCalendar and once as DischargeCalendar. Each instance should have its fields appropriately aliased to reflect whether they pertain to Admission or Discharge dates.
* Load the Encounters tableas usual, but now you have two separate calendar tables that can be linked to the appropriate date fields (AdmissionDate and DischargeDate) in the Encounters table.
This approach ensures:
* Users can filter both AdmissionDate and DischargeDateindependently using the fields in their respective calendar tables.
* Only relevant datesassociated with actual encounters will be available for filtering, as the calendars are linked specifically to the AdmissionDate and DischargeDate fields.
* Efficiency and clarityin the data model, as the fields from the Master Calendar are distinctly assigned to either Admission or Discharge, avoiding any confusion or incorrect filtering.
This method avoids unnecessary complexity and directly meets the healthcare organization's requirements in a straightforward and scalable manner.

NEW QUESTION # 34
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. Merge
B. Partial Reload
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 # 35
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. Create a composite key using OrderlD and UneNo
B. Remove the LineNo field from both tables and use the AutoNumber function on the OrderlD field
C. Create a composite key using OrderlD and LineNo, and remove OrderlD and LineNo from Shipments
D. Remove the LineNo field from Shipments and use the AutoNumber function on the OrderlD field

Answer: A

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 # 36
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QSDA2024 EXAM SUCCESS, QSDA2024 UPDATED CBT

QSDA2024 Exam Success, QSDA2024 Updated CBT