Unified Data Analytical Engine for Multi-Source Integration
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Solution Overview
Problem
Conventional data analytics and business intelligence systems are complex, expensive, and difficult to adopt, especially for small and medium businesses, due to the need for disparate tools and skillsets, which hinders AI adoption and efficient decision-making across various industries.
Innovation Solution
A data analytical engine system that combines data from multiple sources into a unified, manipulable format, providing customizable AI models, machine learning algorithms, and real-time analytics, enabling efficient data visualization and recommendation capabilities without requiring extensive technical expertise or multiple systems integration.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If conventional data analytics systems use multiple disparate tools and skillsets to meet industry-specific needs, then the system can handle diverse data requirements, but the device complexity and cost increase significantly
Solution Approach 1:
The patent implements a universal data analytics platform that can handle multiple industry-specific requirements (banking, healthcare, manufacturing, retail) through a single integrated system. The platform uses common data structures, unified authentication mechanisms, and standardized visualization capabilities that work across all industries, eliminating the need for disparate tools while maintaining adaptability to sector-specific needs
2Adaptability or versatility
If conventional systems mix and match disparate tools to address specific industry needs, then the system can be customized for each industry, but the ease of operation and adoption become difficult
Solution Approach 1:
The patent segments the data analytics platform into modular components including data source connectors, authentication modules, data structure templates, machine learning algorithm libraries, and visualization generators. Each module can be independently configured for different industries while maintaining a unified interface, allowing easy adoption through selective activation of industry-specific features without requiring complete system reconfiguration
3Adaptability or versatility
If conventional data analytics systems integrate multiple disparate tools, then the system can provide comprehensive data processing capabilities, but the productivity and decision-making speed are reduced
Solution Approach 1:
The patent merges data processing, analysis, and visualization functions into a single integrated workflow. Data flows continuously from multiple sources through unified processing pipelines to generated visualizations and insights without manual intervention between separate tools. This consolidation maintains comprehensive processing capabilities while significantly improving productivity by eliminating the time required to transfer data between disparate systems and the expertise needed to operate multiple tools
Data Source
AI summary
A system includes a memory storing computer-readable instructions and at least one processor to execute the instructions to receive database authentication information from a client computing device, obtain data from a first data source using the database authentication information, the first data source storing data having a first representation of the data, store the data in a second data source, the second data source having a second representation of the data that is different from the first representation of the data, receive a request to create a visualization of the data and generate a visualization of the data using the second representation of the data, and transmit the visualization of the data to the client computing device.