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Qlik Sense Data Architect Certification Exam - 2024 Sample Questions (Q32-Q37):

NEW QUESTION # 32

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

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 # 33
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. FileExists, FOR EACH, IF
B. FilePath, IF, THEN, Drop
C. FileSize, IF, THEN, END IF
D. FilePath, FOR EACH, Peek, Drop

Answer: A

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 # 34
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 record creation time, a secondary key field to remove deleted records, configure reload task to load four times a day
B. A field with ModificationTime, a primary key field to sort out updated records, insert and append records, update records
C. 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
D. A field with ModificationTime, a primary key field to sort out updated records, insert and update records, remove records

Answer: D

Explanation:
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.

NEW QUESTION # 35
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. IntervalMatch
C. Partial Reload
D. Semantic

Answer: B

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 # 36
A Chief Information Officer has hired Qlik to enhance the organization's inventory analytics. In the initial meeting, the client's focus was determined to be forecasting inventory levels.
Which stakeholder should be consulted first when gathering requirements?

A. Vice President of Marketing
B. SQL Developer
C. Product Buyer
D. Chief Information Officer

Answer: C

Explanation:
In this scenario, the focus of the project is to enhance inventory analytics, specifically targeting forecasting inventory levels. The primary goal is to understand the factors influencing inventory management and to build a model that helps in predicting future inventory needs.
Option A: Product Buyeris the correct stakeholder to consult first.
Here's why:
* Direct Involvement in Inventory Management:
* The Product Buyer is typically responsible for making decisions related to purchasing and maintaining inventory levels. They have a deep understanding of the factors that influence inventory needs, such as lead times, supplier reliability, demand forecasting, and purchasing cycles.
* Knowledge of Inventory Requirements:
* Since the project's primary focus is forecasting inventory levels, the Product Buyer will provide crucial insights into the variables that affect inventory and the data needed for accurate forecasting. They can guide what historical data is essential and what external factors might need to be considered in the forecasting model.
* Alignment with Business Objectives:
* By consulting the Product Buyer, the project can ensure that the inventory forecasting models align with the company's inventory management objectives, avoiding overstocking or understocking, and thus optimizing costs.
References:
* Qlik Project Management Best Practices: In analytics projects, particularly those focused on specific operational areas like inventory management, consulting the stakeholders who are closest to the operational data and decision-making processes ensures that the solution will be relevant and effective.

NEW QUESTION # 37
......

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