Blended Data Retrieval in Normalized Models
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Solution Overview
Problem
Current data processing and visualization technologies require separate software applications for different data sources, making it difficult to view and compare data from multiple sources using a single chart or visualization, as each source may have different formats or structures.
Innovation Solution
A method that generates analytic queries for multiple data sources with different schemas or formats, converts results to a standardized schema, and executes a blend query to combine data from these sources, allowing for unified visualization without data replication.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If separate software applications are used for different data sources, then each data source can be accessed with its native format and structure, but it becomes difficult to view and compare data from multiple sources using a single chart or visualization
Solution Approach 1:
The patent introduces a data blending layer that acts as an intermediary between multiple data sources and the visualization interface. This blending layer receives data from various sources in different formats, standardizes and integrates them, then provides unified access through a single query interface, eliminating the need for separate applications while maintaining native data source capabilities
Solution Approach 2:
The system creates a universal data access interface that can handle multiple data sources with different formats and structures through a single standardized query language. The blending layer provides multi-functional capabilities to translate, transform, and integrate diverse data sources into a unified view accessible through one application
2Reliability
If data from different sources with different formats is to be visualized, then separate applications are required, but this requires users to prepare and compare data from multiple charts separately
Solution Approach 1:
The system performs preliminary data standardization and integration in the blending layer before visualization. Data from multiple sources is pre-transformed into a unified schema with consistent data types and structures, so when users create visualizations, the data is already prepared and ready for immediate comparison across sources without separate preparation steps
3Productivity
If data replication among data sources is avoided, then data maintenance is simplified, but it becomes challenging to retrieve and combine data from diverse sources with different schemas
Solution Approach 1:
The system changes the parameter of data representation by introducing a virtual unified schema that maps to various physical data source schemas. The blending layer dynamically transforms query parameters and data formats on-the-fly, allowing efficient data retrieval from diverse sources without replication while managing schema differences through parameter transformation rather than structural complexity
Data Source
AI summary
Techniques and solutions are described for performing analytics on, or generating displays based on, data retrieved from a plurality of data sources, where the data sources can use one or both of different execution formats or different data schemas. For selected data, one or more analytic queries are generated. Analytic query results are provided in a standardized schema. A blend query is executed against data from the plurality of data sources, including the analytic query results in the standardized schema. Disclosed technologies can facilitate the use of data maintained in different formats or maintained in data sources that have different execution formats or protocols without requiring data replication among the data sources. The disclosed technologies can also provide a platform to which new data sources can easily be added, and can facilitate the use of multiple data sources by non-technical users.