QSBA2024 Exam Dumps : Qlik Sense Business Analyst Certification Exam-2024

In scenarios where a customer needs to standardize colors across multiple apps and be able to update them quickly, usingvariablesin combination with aninclude statementis the most flexible and maintainable approach.

A. Design all base objects as master visualizations and link each object in each app to the relevant master visualization.While master visualizations help with consistency within a single app, they don't offer an easy way to update all apps globally. You would need to manually update the colors in every master visualization in each app, which is not efficient for large-scale management.

B. Develop the first app with every variation of object and visualization and duplicate this app.Duplicating apps will create maintenance challenges. Each app would need to be updated individually if colors or other settings change, which is not scalable for over 100 apps.

C. Create all color expressions as variables in a text file, load it in each app with an include statement, and use these variables in the color property of all objects.This is the most efficient solution. By storing color definitions in a text file and loading them with aninclude statement, the business analyst can update the colors in one place, and these updates will be reflected across all apps that use the file. This method ensures easy maintenance and flexibility.

D. Store color definitions within a .qvd file and load it as a data island.While using a .qvd file is possible, it’s not as straightforward as using variables and an include statement. Data islands are typically used for selection purposes, and this method would introduce unnecessary complexity in managing colors.

Key Qlik Sense Business Analyst References:

Variablesare widely used in Qlik Sense for managing repeated expressions or values like colors. They can be defined once and reused throughout the app.

Include statementsallow external files (like text files containing variables) to be loaded into apps, ensuring that updates made to the text file are automatically reflected in all apps that use it. This creates a flexible and scalable solution for managing standardization across multiple apps.

Thus, the best way to maintain a standardized color palette across all apps is tocreate all color expressions as variables in a text file and load them into each app using an include statement.

For this scenario, using abar chart,scatter plot, andhistogramprovides the best coverage of the requirements. Thebar chartis ideal for comparing the sales performance of the top 10 sales representatives. Thescatter plotis used to analyze the relationship between margin percentage and total sales by product category. Thehistogramis excellent for visualizing the distribution of sales amounts.

Key Concepts:

Bar Chart: Perfect for comparing categorical data, such as sales amounts across different sales representatives.

Scatter Plot: Ideal for exploring relationships between two variables, such as margin percentage and total sales.

Histogram: Provides a clear visualization of the distribution of a continuous variable, such as sales amounts.

Why the Other Options Are Less Suitable:

B. Treemap, Container, and Distribution plot: A treemap is less effective for comparing individual sales reps, and a container does not provide a clear visualization on its own.

C. Bar chart, Line chart, and Scatter plot: A line chart is not needed in this case, as it is best for showing trends over time, which is not required here.

D. Treemap, Box plot, and Histogram: A box plot is more suited for showing statistical distributions (e.g., quartiles), which is unnecessary in this case.

References for Qlik Sense Business Analyst:

Data Exploration: Bar charts, scatter plots, and histograms are among the most commonly recommended visualizations for comparing performance, analyzing relationships, and viewing distributions in Qlik Sense.

Thus, the combination of abar chart,scatter plot, andhistogramoffers the most comprehensive solution, makingAthe correct answer.

The app is experiencing performance issues due to inefficient calculations in a master measure that processes the field TransactionName, which has a complex structure (e.g., "1_ABCDEFGHI_23454"). Let’s analyze the available options and whyOption Bis the best solution.

A. Ask the developer of the underlying database to change the structure of the field TransactionName.While modifying the data structure in the underlying database might improve performance, this approach is not ideal. It’s a time-consuming process that might not be feasible, especially when working with large datasets that have already been integrated into the Qlik Sense app. The performance improvement should focus on optimizing the Qlik app itself.

B. In the Data manager, use the Split function to split the field values with the underscore character as the separator. In the Data manager, use the Add calculated field function to multiply the 1st and the 3rd column of the split field. Reload the data.This is the most efficient approach. By using theSplit functionin the Data Manager to break down the TransactionName field based on the underscore separator, the data becomes more accessible for calculations. You can then create a calculated field that multiplies the first and third components of the split data (corresponding to the 1st part and the numeric identifier at the end). This reduces the need for complex string manipulation functions (e.g., Left, Right, Trim) within the master measure, which can be resource-intensive when applied to large datasets.

C. Change the master measure definition as follows: subfield( TransactionName, '',!) * subfield( TransactionName, '', 3)This option suggests using thesubfield() functionto split the string within the master measure itself. While this approach is valid, it doesn’t provide as significant a performance improvement compared to pre-processing the data in theData Manager. Calculating fields directly within the visualizations is more computationally expensive compared to handling it during the data load phase.

D. In the Data manager, use the Replace function to remove the middle part of the field TransactionName.TheReplace functionwould remove the middle section of the transaction name, but it doesn’t address the need to split the field for efficient multiplication. It would also result in a loss of important data that may be required for other analyses.

Key Qlik Sense Business Analyst References:

TheData Managerprovides powerful tools for transforming and optimizing data before it is used in visualizations. Pre-processing the data using functions likeSplitsignificantly reduces the load on front-end visualizations.

Splitting fields during the data load rather than in the master measures improves performance, especially in large datasets where string manipulation functions in visualizations can degrade performance.

Calculated fieldsallow analysts to create new expressions based on transformed data, ensuring that the app remains efficient while meeting analytical needs.

Thus, the correct solution is touse the Split function to separate the field values and then use a calculated field to multiply the required components, which enhances app performance.