A business analyst receives multiple requests for a variety of different filter panes to be placed on a dashboard. Users need to filter on many different values across different fields.
Which Qlik Sense feature do the users need to learn about to meet their needs?
When users need to filter across many different fields and values in a Qlik Sense dashboard, the most efficient feature they can use is Smart Search. Smart Search allows users to quickly search across all fields within the data model, enabling them to find relevant information and apply filters in a streamlined manner.
A . Smart search This is the correct option. Smart Search enables users to enter search terms and find matches across all fields in the data model, allowing for quick and intuitive filtering. It helps users locate specific data points or filter across multiple fields at once, making it highly efficient when multiple filter panes are needed.
B . Data model viewer The Data Model Viewer provides a visual representation of the relationships between data tables in the model. While it's useful for understanding the data structure, it's not a tool for filtering or user interaction with data.
C . Insight Advisor The Insight Advisor is designed for guided analytics, providing suggestions and generating visualizations based on user queries. It does not offer the comprehensive filtering capabilities that Smart Search does.
D . Governed self-service Governed self-service refers to the balance between providing users with flexibility in creating their own visualizations while maintaining control over data governance. It's not related to filtering or searching data in the same way as Smart Search.
Key Qlik Sense Business Analyst References:
Smart Search in Qlik Sense is designed to provide fast, interactive search capabilities that span across all fields, enabling complex filtering in an easy-to-use interface.
This feature allows users to filter multiple fields simultaneously, saving time and effort when analyzing diverse data sets.
Thus, the correct feature for filtering on multiple values across different fields is Smart Search.
A business analyst is creating an app for the team. A set of selections must be applied every time an app is opened. Which action should the business analyst take to meet this requirement?
In Qlik Sense, default bookmarks allow a set of selections to be applied automatically whenever the app is opened. By creating a bookmark and setting it as the default, the business analyst ensures that the required selections are applied every time the app is opened, which meets the requirement of consistently applying the same selections for all users.
Key Concepts:
Default Bookmark: A default bookmark automatically applies the saved selections when an app is opened, ensuring consistency without manual input from users.
Bookmarking: This feature allows users to save specific selections or states of a dashboard for later use.
Why the Other Options Are Less Suitable:
A . Section Access: Section Access controls data access and security, not default selections.
B . Mashup with API: While this could technically work, it's unnecessarily complex and requires custom coding.
C . Sheet Action: A sheet action could apply a bookmark but would not ensure that the selections are applied at the time of app opening.
References for Qlik Sense Business Analyst:
Default Bookmark for Predefined Selections: This feature is commonly used to ensure that specific selections are always applied when an app is opened.
Thus, D is the best solution for applying default selections, making it the correct answer.
A business analyst from the APAC region is creating a single KPI object for that region.
The analyst must meet the following requirements:
* The KPI should show a total of sales
* The business wants to compare current year (CY) vs last year (LY) sales
* The KPI should not change if the user makes selections
Which measure(s) will allow the KPI object to fulfill this requirement?
A)
B)
C)
D)
For the KPI object that meets the requirements of comparing Current Year (CY) sales against Last Year (LY) sales, while ensuring the KPI remains static regardless of selections, we need to leverage Set Analysis with the 1 identifier. This ensures the KPI ignores any selections made by the user.
Option A uses the correct structure of Set Analysis that compares CY sales to LY sales within the APAC region, and the 1 set identifier ensures the KPI does not change based on selections. The logic is structured as follows:
Sum({1 <region={'apac'}, year={$(=max(year))}>} Sales) computes the sales for the APAC region for the current year (CY).
Sum({1 <region={'apac'}, year={$(=max(year)-1)}>} Sales) computes the sales for the APAC region for the previous year (LY).
This expression will ensure that the comparison of sales between CY and LY is made, without being affected by user selections.
Key Concepts:
Set Analysis with 1: The 1 set identifier ensures that selections made by users do not affect the result, making the KPI static.
Comparison of CY vs. LY: The use of $(=max(year)) and $(=max(year)-1) ensures that the current and previous years are dynamically compared.
Why the Other Options Are Less Suitable:
B, C, and D: While these options use a similar structure, they do not correctly handle the measure structure or have syntactical issues. Only Option A properly utilizes the 1 set identifier and dynamic year comparison for the APAC region.
References for Qlik Sense Business Analyst:
Set Analysis for Static KPIs: Using the 1 set identifier in Qlik Sense ensures that a KPI remains static and unaffected by user selections, which is essential for business requirements like this.
Thus, A is the correct choice because it correctly computes the required static KPI for the APAC region, making it the verified answer.
The VP of Sales asks a business analyst to include a KPI object on the sales dashboard that shows total sales value for the year 2022, regardless of selections. Existing fields in the data model include Sales and Year.
How should the business analyst write the measure for the KPI object?
In this scenario, the VP of Sales wants to see the total sales for the year 2022 regardless of selections. This requirement is best handled using Set Analysis in Qlik Sense. The key to achieving this is using the set identifier 1, which ignores the user's selections and ensures the calculation is based on the entire dataset. The expression Sum( { 1 < year = { '2022' } > } Sales) calculates the sum of sales for the year 2022, irrespective of any other selections made in the app.
Key Concepts:
Set Identifier 1: This identifier ensures that the calculation is performed on the entire dataset, ignoring any selections or filters applied by the user.
Year Filtering: The expression < year = { '2022' } > ensures that only sales from the year 2022 are included in the calculation.
Why the Other Options Are Less Suitable:
A . Sum( { < year = '2022' > } Sales): This is incorrectly formatted, and the pipe (|) symbol should not be used in this context.
B . Sum( { $ < year = { '2022' } > } Sales): The $ set identifier respects the current selections, which is not what is needed in this case, as the VP wants the value to be shown regardless of selections.
D . Sum( 1 { < year = { '2022' } > } Sales): The placement of 1 is incorrect in this expression.
References for Qlik Sense Business Analyst:
Set Analysis: Qlik Sense's Set Analysis allows analysts to control what data is used in a calculation, regardless of user selections. The set identifier 1 ensures that selections are ignored, which is essential for showing fixed data such as total sales for a specific year.
Thus, the correct expression to show the total sales for 2022, regardless of user selections, is C.
A business analyst needs to rapidly prototype an application design for a prospective customer. The only dataset provided by the customer contains 30 fields, but has over one billion rows. It will take too long to keep loading in its entirety while the analyst develops the data model.
Which action should the business analyst complete in the Data manager?
When working with large datasets, such as the one containing over a billion rows in this scenario, loading the entire dataset can be time-consuming, especially during the development phase. Qlik Sense provides a Filter data option in the Data Manager, which allows business analysts to work with a subset of the data during development. This is particularly useful for rapidly prototyping the application design.
Key Concepts:
Filter Data Option: This feature in Qlik Sense allows the analyst to load a smaller sample of the dataset for analysis and development purposes. By filtering out unnecessary rows, the business analyst can quickly build and prototype the application without waiting for the full dataset to load. Once the design is finalized, the full dataset can be reloaded.
Prototyping with Reduced Data: It's often more efficient to work with a smaller dataset during the design phase. This allows for faster iterations and design cycles, especially when working with large datasets.
Why the Other Options Are Less Suitable:
A . Split the dataset and create a normalized star schema of associated tables: This would involve complex data modeling that is not necessarily related to the immediate need of reducing the size of the dataset for prototyping. While star schemas can optimize data models, it's not the quickest way to reduce the number of rows for initial testing.
B . Deselect text columns with unique data values to reduce the memory footprint: This may reduce the memory usage but won't necessarily address the issue of reducing the number of rows. Also, the text columns might be important for the analysis and should not be removed without careful consideration.
D . Truncate text fields longer than 256 characters to create preview fields: Truncating text fields will not significantly reduce the dataset size or the load time. It may also result in losing critical information, which is not ideal for prototyping.
References for Qlik Sense Business Analyst:
Rapid Prototyping: Qlik Sense encourages rapid development of applications by allowing business analysts to work with subsets of the data. The Filter Data option is an important tool for managing large datasets efficiently.
Data Manager Tools: The Data Manager in Qlik Sense provides several tools for reducing the dataset size, and filtering is one of the key options for improving performance during development.
Using the Filter data option allows the business analyst to focus on a smaller subset of data, enabling quicker prototyping and iteration, which makes option C the most effective solution.
