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Qlik Sense Data Architect Certification Exam - 2024 Sample Questions (Q51-Q56):

NEW QUESTION # 51
A data architect inherits an app that takes too long to load and overruns the data load window.
The app pulls all records (new and historical) from three large databases. The reload process puts a heavy load on the source database servers. All of the data is required for analysis.
What should the data architect do?

A. Make sure the individual reload tasks in the QMC are not running in parallel
B. Implement Direct Discovery with partial load
C. Implement ODAG to split out the app into smaller chunks
D. Implement incremental load on each database using QVD files

Answer: D

Explanation:
The scenario describes an app that is experiencing long load times due to the need to pull all records, both new and historical, from three large databases. This situation puts a strain on both the Qlik environment and the source databases. Given that all data is required for analysis, a full reload each time can be inefficient and resource-intensive.
Implementingincremental loadis a widely recommended approach in such cases. Incremental loading allows you to load only new or changed data since the last reload, rather than reloading all the data every time. This significantly reduces the time and resources required for reloading, as only a subset of the data needs to be processed during each reload. QVD (QlikView Data) files are typically used to store the historical data, while only the new or updated records are fetched from the source databases.
This approach would help:
* Reduce the load on the source databases.
* Shorten the data reload window.
* Maintain historical data efficiently while ensuring that all new data is captured.

NEW QUESTION # 52
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:486396169. 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. FileSize, IF, THEN, END IF
B. FilePath, FOR EACH, Peek, Drop
C. FileExists, FOR EACH, IF
D. FilePath, IF, THEN, Drop

Answer: C

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 # 53
A data architect executes the following script:

What will be the result of Table.A?

Answer: C

Explanation:
In the script provided, there are two tables being loaded inline: Table_A and Table_B. The script uses the Join function to combine Table_B with Table_A based on the common field Field_1. Here's how the join operation works:
* Table_Ainitially contains three records with Field_1 values of 01, 01, and 02.
* Table_Bcontains two records with Field_1 values of 01 and 03.
When Join(Table_A) is executed, Qlik Sense will perform an inner join by default, meaning it will join rows from Table_B to Table_A where Field_1 matches in both tables. The result is:
* For Field_1 = 01, there are two matches in Table_A and one match in Table_B. This results in two records in the joined table where Field_4 and Field_5 values from Table_B are repeated for each match in Table_A.
* For Field_1 = 02, there is no corresponding Field_1 = 02 in Table_B, so the Field_4 and Field_5 values for this record will be null.
* For Field_1 = 03, there is no corresponding Field_1 = 03 in Table_A, so the record from Table_B with Field_1 = 03 is not included in the final joined table.
Thus, the correct output will look like this:
* Field_1 = 01, Field_2 = AB, Field_3 = 10, Field_4 = 30%, Field_5 = 500
* Field_1 = 01, Field_2 = AC, Field_3 = 50, Field_4 = 30%, Field_5 = 500
* Field_1 = 02, Field_2 = AD, Field_3 = 75, Field_4 = null, Field_5 = null

NEW QUESTION # 54
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?

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

Answer: 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 recordsfor 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.

NEW QUESTION # 55
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. Semantic
B. Merge
C. IntervalMatch
D. Partial Reload

Answer: C

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 # 56
......

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2025 UPDATED EXAM QSDA2024 ONLINE | QSDA2024 100% FREE QUESTIONS

2025 Updated Exam QSDA2024 Online | QSDA2024 100% Free Questions