Middleware Database Dimensional Data Transforms
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Solution Overview
Problem
Existing middleware platforms struggle to effectively aggregate and transform data from multiple sources with different dimensions and formats to meet the diverse data requirements of various applications.
Innovation Solution
A middleware database system that hosts dimensional transforms, allowing it to receive data requests, identify data types, and store links to remote data sources, transforming data dimensions as needed to generate compatible output for different applications, including OLAP, object-oriented, and relational formats.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a middleware platform attempts to aggregate and transform data from multiple sources with different dimensions and formats, then data compatibility and accessibility are improved, but system complexity increases
Solution Approach 1:
The patent introduces a middleware database as an intermediary component between diverse data sources and applications. This middleware hosts dimensional transforms that automatically convert data from different sources into a unified format, eliminating the need for complex custom integration logic and reducing overall system complexity while maintaining high data compatibility
Solution Approach 2:
The middleware database is designed with universal functionality to handle multiple data sources, various data formats, and different application requirements through a single platform. By implementing dimensional transforms that work across different data types and structures, the system achieves broad adaptability without proportionally increasing complexity
2Adaptability or versatility
If dimensional transforms are hosted in the middleware database to transform data dimensions, then data transformation capability is improved, but processing time increases
Solution Approach 1:
The middleware database pre-hosts dimensional transforms and prepares transformation logic in advance. By having transforms readily available and pre-configured in the middleware, the system can immediately begin data transformation operations without delays associated with dynamic compilation or interpretation, thus maintaining high transformation capability while minimizing processing time
Solution Approach 2:
The system uses dimensional transforms that create standardized copies of data in the required format. Rather than repeatedly processing original data from multiple sources, the middleware creates transformed copies once and serves these to multiple applications, reducing redundant processing time while maintaining full transformation capability
3Ease of operation
If the middleware database stores links to remote data sources and transforms data on demand, then data accessibility is improved, but data consistency may deteriorate
Solution Approach 1:
The middleware database acts as a trusted intermediary that manages connections to remote data sources and applies consistent transformation rules to all data. This centralized control ensures that regardless of where data originates or how it is accessed, the same dimensional transforms are applied, maintaining data consistency while preserving easy accessibility through the unified interface
Solution Approach 2:
The system applies parameter changes through dimensional transforms that standardize data format, structure, and dimensions. By transforming data parameters to a common schema at the middleware layer, the system ensures consistency across all accessed data while maintaining the ability to retrieve data from diverse remote sources
Data Source
AI summary
Embodiments relate to systems and methods for a middleware database hosting dimensional transforms. A set of applications can access a combined data of a set of data sources via a database system. The set of data sources can be configured with diverse dimensions and associated data. The requesting application(s) can generate a request to the database system to extract data in compatible formats for the application(s). In embodiments, the database system can transform selected dimensional data (e.g., company, year, sales dimensions) from the data sources into transformed dimensional data. The requesting application(s) can therefore perform searches, sorts, and/or other operations on the transformed dimensional results.