Dynamic Data Management for Unstructured Database Transformation
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Solution Overview
Problem
The complexity of unstructured data generated by machines and IT systems makes it difficult for users to access, comprehend, and manipulate, as existing technologies struggle to transform this data into a structured format that users can easily work with.
Innovation Solution
A system and method that transform unstructured data from a distributed, non-relational database into a structured format, allowing users to query and manipulate the data using a transformation module that creates a relational database table based on user queries, enabling users to access and analyze the data without needing to understand the complex unstructured format.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If unstructured data is stored in a distributed non-relational database, then data storage capacity and flexibility are improved, but data accessibility and ease of manipulation deteriorate
Solution Approach 1:
The patent introduces a transformation module as an intermediary between the unstructured data storage system and user queries. This module dynamically transforms unstructured data into structured formats (such as SQL tables) that users can easily query and manipulate, while the underlying unstructured data remains stored in its flexible non-relational format. The transformation module acts as a mediator that translates between the flexible storage format and the structured access format.
Solution Approach 2:
The system segments the data handling process into two distinct layers: a storage layer that maintains unstructured data in its native flexible format, and an access layer that transforms data into structured formats for querying. This segmentation allows each layer to optimize for its specific function without compromising the other.
2Reliability
If unstructured data is constantly generated and changed, then data currency and relevance are improved, but data complexity and difficulty of access increase
Solution Approach 1:
The transformation module is designed to be dynamic, automatically adapting to changes in the unstructured data format and structure. When new types of unstructured data are introduced or existing data formats change, the transformation module dynamically adjusts its transformation logic to maintain structured output formats, allowing the system to handle constantly changing data without increasing user-facing complexity.
Solution Approach 2:
The transformation module performs self-adjustment by automatically detecting changes in unstructured data formats and adapting its transformation rules accordingly. This self-service capability eliminates the need for manual intervention when data formats evolve, maintaining data accessibility despite continuous changes.
3Ease of operation
If unstructured data is transformed into structured format dynamically, then user accessibility is improved, but processing time and computational resources increase
Solution Approach 1:
The system performs preliminary transformation by pre-processing unstructured data into intermediate structured formats and caching these transformations. When users query the data, the system can retrieve pre-transformed data structures rather than performing complete transformations from scratch, significantly reducing query response time while maintaining full accessibility.
Solution Approach 2:
The transformation module adjusts transformation parameters and depth based on query requirements. For simple queries, it performs minimal transformation, while for complex queries requiring more detailed structured data, it performs more extensive transformation. This parameter-based adaptation optimizes processing time based on actual user needs.
Data Source
AI summary
An interface for users to gain access and manipulate unstructured data is provided. In response to receiving a user query associated with a first database format, a system can request unstructured data associated with a second database format from a second database. The unstructured data can include a set of data groups where each data group has a set of values. Each value can be associated with a different tag. To generate a structured database, some embodiments can determine the number of data groups and the number of unique tags across the data groups and populate the table with data from the unstructured data. Subsequently, the system can apply the user query to the table to obtain a query result and transmit the query result to the user device.