AIV Global Filter Buddy
AIV Global Filter Buddy simplifies the process of applying and managing filters across all widgets on a dashboard. By converting natural language prompts into AlaSQL queries, this tool ensures consistent and effective filtering of data across various visualizations. Note that the global filter functionality is available only in preview mode, not in edit mode.
Key Features
- Global Filter Application: Apply filters universally across all widgets on a dashboard with a single command. AIV Global Filter Buddy translates natural language requests into AlaSQL queries that are then applied to each widget, ensuring cohesive data filtering.
- Natural Language Processing: Describe filtering needs in plain English, and AIV Global Filter Buddy will convert these descriptions into precise AlaSQL queries. This process allows for intuitive and efficient filter application without the need for manual query writing.
- Automatic Query Generation: Based on the input prompt, the tool automatically generates the necessary AlaSQL query to filter data. This eliminates the need for manual query construction and ensures that all relevant widgets reflect the applied filter.
- Contextual Query Expansion: If the next query is related to the previous one, AIV Global Filter Buddy will intelligently expand the AlaSQL query to include the new conditions, allowing for seamless, contextual filtering across sessions.
- Comprehensive Widget Filtering: The tool ensures that all widgets on the dashboard are updated according to the specified filter, maintaining consistency across different data visualizations.
- Speech to Text Integration: Convert spoken language into filter prompts. Simply speak desired filter criteria, and AIV Global Filter Buddy will transcribe the speech into text and generate the corresponding AlaSQL query. This feature provides a hands-free way to manage dashboard filters.
- Clear Filters:
- From Individual Widgets: Remove filters from specific widgets with ease. Users can specify which widget to clear the filter from, allowing for targeted adjustments.
- From All Widgets at Once: Clear filters from all widgets simultaneously, resetting the dashboard to its default state without any active filters.
- Query History: Maintain a history of applied filters and generated AlaSQL queries. Users can review previous filters, allowing for easy reuse or modification of past filter settings. This history helps track filter application and refine data views as needed.
- Copy Results: Easily copy the generated AlaSQL queries to the clipboard. This feature allows users to quickly transfer the query for use in other applications or for further processing, facilitating integration with different systems or documentation.
- Initiate New Chat: Start a new session to create a completely new filter without referencing previous queries. This feature clears the current context and allows for a fresh prompt and response, making it easy to apply new, unrelated filters.
Follow these steps to utilize the AIV Global Filter Buddy
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Open the dashboard. Here, we have one Defence Equipment Revenue dashboard. Users can select the dashboard according to their requirements.
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Click on the Global Filter icon at the top-right corner of the screen, as shown in the figure below.
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Click on the AI Tab in the AIV Global Filter Buddy, as shown in the figure below.
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Write the prompt to filter the dashboard. For example, to display data from the USA, use the prompt: Display data for the USA.
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After writing the prompt, click on the prompt input button to apply the prompt to the dashboard, as shown in the figure below.
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The prompt will be automatically applied when the user clicks on the prompt input button, as shown in the figure below.
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Also, users can do contextual filtering by adding more prompt as shown in figure below:
- Example: Show data from the year 2002.
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To edit the query, the user can edit the applied query from the Filters tab, as shown in the figure below.
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Click on the
edit icon
in the Action box of the query. The query will be displayed in the text box automatically, as shown in the figure below. -
Edit the query to [Year] = ‘2005’ instead of ‘2002’, as shown in the figure below.
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After editing the query, the user needs to click on the prompt input button to apply the query.