Synthetic Data Aggregation Wizard for Disparate Datasets
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Solution Overview
Problem
Conventional data aggregation platforms struggle to manage and present disparate datasets that do not naturally fit into traditional time series formats, leading to technical difficulties in real-time data distribution, incomplete data presentation, and increased computational burden, especially with rapidly changing and large volumes of data.
Innovation Solution
Systems and methods for aggregating disparate data into a singular datapoint using a synthetic aggregation wizard, enabling user-customizable data mapping, filtering, and display through an interactive GUI, supporting dynamic real-time updates and historical time series.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If conventional data aggregation platforms use traditional time series formats and workflows, then data presentation is standardized, but datasets that do not naturally fit into these formats cannot be easily presented or managed
Solution Approach 1:
The patent introduces an intermediary layer (data normalization service and synthetic symbol engine) that sits between the diverse data sources and the traditional time series workflow. This intermediary automatically transforms disparate datasets into a standardized format, allowing the system to handle diverse data types without increasing user-facing complexity or requiring manual intervention for each data type.
2Speed
If real-time data distribution is implemented with increasing data volume and volatility, then data freshness is improved, but transmission and data handling delays introduce significant errors
Solution Approach 1:
The system performs preliminary actions by pre-normalizing data schemas and pre-establishing aggregation workflows before real-time data arrives. The synthetic symbol engine pre-configures the transformation rules, so when real-time data streams in, the normalization and aggregation happen automatically without delays, maintaining both speed and accuracy.
3Loss of information
If traditional workflows require identifier definition with associated history for each data type, then data traceability is maintained, but the amount of key-value-pairs becomes effectively infinite and difficult to search and maintain
Solution Approach 1:
The patent creates a universal identifier system where synthetic symbols serve multiple functions: they uniquely identify data points, encode aggregation logic, and provide searchable metadata. Instead of creating separate identifier systems for each data type, the synthetic symbol engine generates unified identifiers that work across all disparate datasets, making them searchable and maintainable while preserving full data history through the standardized format.
4Device complexity
If one-size-fits-all conventional platforms use fixed filters for data retrieval, then system simplicity is maintained, but datasets with attributes that do not align with platform filters lack relevant information or are incomplete
Solution Approach 1:
The system implements dynamic filter generation where the aggregation wizard automatically adapts filter criteria based on the specific characteristics of each disparate dataset. Rather than using fixed filters, the system dynamically adjusts the retrieval parameters to match the data attributes, ensuring complete and relevant information is captured while maintaining automated simplicity through the wizard interface.
Data Source
AI summary
Systems and methods for aggregating data. The system is configured to receive metadata from an interactive graphical user interface (GUI) of a user device, aggregate field values from the data stored on one or more databases based on the received metadata and generate filter instructions based on the received metadata. The system is further configured to transmit the aggregated field values and the filter instructions to the user device, receive a user-customized filter set and subscription request for a synthetic symbol associated with the user-customized filter set from the user device, and create the synthetic symbol responsive to the subscription request. Moreover, the system aggregates one or more data values from the data stored on the databases associated with the created synthetic symbol and generates instructions to display the data values on the interactive GUI in accordance with the user-customized filter set associated with the created synthetic symbol.