Dashboards
Empower Data Analysts with Effortless Dashboard Building
Data visualization is an integral part of data analysis, as it allows users to derive insights and communicate findings effectively. However, creating visually appealing and informative dashboards traditionally involved time-consuming manual processes. With our groundbreaking feature of Natural Language to Dashboard Creation , data analysts can effortlessly build dynamic dashboards using Key Performance Indicators (KPIs) expressed in plain language, all powered by Superset, an open-source data visualization tool.
Below are the steps involved in the dashboard creation process :-
Select Datasource and Dashboard Description
The user starts by selecting a data source from which they want to create a dashboard.
They provide a description or title for the dashboard, outlining its purpose or key focus.
Add KPIs Using Natural Language
Using the Natural Language Dashboard Creation feature, the user adds Key Performance Indicators (KPIs) to the dashboard by expressing their requirements in plain language.
The system generates SQL queries based on the natural language inputs and displays a preview of the resulting data in real-time on the right-hand side .
The user has the option to review the generated SQL queries and validate the results presented in the preview section
If needed, the user can manually modify the SQL queries to fine-tune the data retrieval or apply custom logic for more advanced data processing.
To further enhance the dashboard's visual appeal and user experience, the user can provide design instructions, such as specifying the chart types, color schemes, layout, and other visual elements.
An API connects to Superset, the open-source data visualization tool, and adds the specified charts to the dashboard based on the SQL queries and design preferences.
Further enhance Charts in Superset
Once the charts are added to the dashboard, users have the flexibility to explore and edit the charts further within Superset.
With Superset's rich features, users can perform fine-grained customization, apply additional data filters, and create interactive dashboards tailored to their unique analytical needs.
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