Dashboard Builder Live Data Updating Without Exiting Edit Mode
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Solution Overview
Problem
Existing systems do not provide real-time business analytics for large volumes of data, limiting businesses' ability to make informed decisions through live data rendering and flexible data analysis.
Innovation Solution
A platform for ultra-fast, ad-hoc data exploration and faceted navigation on integrated, heterogeneous data sets, enabling live data rendering on a live dashboard with animated informational morphing replay and declarative data visualization, allowing analysts to create and update dashboards without exiting edit mode.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If real-time data rendering is implemented for large volumes of data, then business analytics capability is improved, but system performance and processing speed deteriorate
Solution Approach 1:
The system segments large data volumes into smaller manageable chunks that can be processed and rendered in real-time. Dashboard panels are divided into discrete data representations that can be independently updated and rendered, allowing the system to handle large datasets without overwhelming processing requirements.
Solution Approach 2:
Data is pre-processed and prepared before being presented to the user. The system performs preliminary data aggregation, filtering, and formatting operations so that when data needs to be displayed, it is already in an optimized state ready for rapid rendering.
2Adaptability or versatility
If live data updating is enabled during dashboard editing, then data freshness and interactivity are improved, but system complexity and resource consumption increase
Solution Approach 1:
The system maintains continuous data updating throughout the dashboard editing process rather than pausing updates. Data continues to flow and refresh in the background while the user edits dashboard elements, ensuring data freshness and enabling users to see real-time effects of their editing actions without requiring mode switches.
Solution Approach 2:
The system introduces an intermediary layer that manages the coordination between live data updates and dashboard editing operations. This intermediary handles data refresh events, coordinates with the editing interface, and manages resource allocation to balance interactivity with system complexity.
3Loss of information
If multiple data sources are integrated for comprehensive analysis, then data completeness is improved, but data integration complexity and processing overhead increase
Solution Approach 1:
The system implements a universal data integration framework that can handle multiple data sources through a common interface and processing pipeline. This multi-functional approach allows diverse data sources to be integrated using the same mechanisms, reducing overall integration complexity while maintaining data completeness.
Solution Approach 2:
The system creates standardized data representations and models that copy essential data structures from various sources into a unified format. This copying approach allows comprehensive data integration while simplifying processing by working with standardized representations rather than dealing with the full complexity of each source system.
Data Source
AI summary
The technology disclosed relates to a platform for ultra-fast, ad-hoc data exploration and faceted navigation on integrated, heterogenous data sets. The disclosed method of declarative specification of visualization queries, display formats and bindings represents queries, widgets and bindings combined on a dashboard in real time, with flexible display options for analyzing data and conveying analysis results.