Odata Driver Transforms Relational Queries for BI Tools
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Solution Overview
Problem
Existing data systems face challenges in accessing and integrating data from various formats, as much data is locked into application-specific formats, making it difficult for business intelligence tools to utilize this data effectively.
Innovation Solution
The Open Data Protocol (Odata) system and method provide access to data sources by using a parsing engine, mapping engine, and Odata driver module to transform relational database requests into Odata queries, enabling business intelligence tools to access and generate reports from Odata data sources, even if the Odata provider does not support all relational database query operations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If data is stored in application-specific formats, then data can be accessed by specific applications, but data becomes difficult to access or integrate into new applications and uses
Solution Approach 1:
The patent implements a universal data access layer that enables business intelligence tools to access data from multiple data sources including OData providers, relational databases, and other formats through a common interface. This universal access mechanism allows the same BI tool to work with different data sources without requiring separate integration logic for each source type.
Solution Approach 2:
The patent introduces an intermediary data access layer that sits between the business intelligence tools and the various data sources. This intermediary layer handles the complexity of data access and integration, translating diverse data source formats into a unified access pattern that BI tools can consume without directly dealing with source-specific complexities.
2Adaptability or versatility
If Odata protocol is used to access data, then data can be unlocked from application-specific formats, but not all relational database query operations are supported by Odata providers
Solution Approach 1:
The patent segments the data access functionality into distinct components: an OData driver module that handles OData-specific operations, a parsing engine that processes queries, and a mapping engine that translates between relational database operations and OData operations. This segmentation allows each component to specialize in handling specific aspects of data access while working together to provide comprehensive functionality.
Solution Approach 2:
The patent introduces a mapping engine as an intermediary that translates relational database query operations into OData operations. This mapping engine acts as a mediator that handles the incompatibility between full relational database query capabilities and OData protocol limitations by converting supported operations and managing the translation process transparently to the user.
3Adaptability or versatility
If business intelligence tools access data from multiple data sources, then data integration capability improves, but the complexity of accessing and transforming data increases
Solution Approach 1:
The patent implements a universal data access architecture where the BI tool can access multiple data sources through a single unified interface. The system provides multi-functional capability to connect to OData providers, relational databases, and other data sources while presenting a consistent access pattern to the user, thereby improving integration capability without proportionally increasing user-facing complexity.
Solution Approach 2:
The patent introduces an intermediary data access layer that manages the complexity of accessing and transforming data from multiple sources. This intermediary layer handles the translation and integration logic, shielding the user from the underlying complexity while enabling comprehensive data source integration through a simplified interface.
Data Source
AI summary
A method for querying an Open Data Protocol (“opendata”) opendata provider includes receiving a relational database query, parsing the relational database query, creating an execution plan, transmitting an opendata query to the opendata provider, transforming a response into a relational format, and providing the transformed response in reply to the relational database query. The method further includes mapping content of an opendata entity data model to a relational model catalog, and processing a portion of the execution plan by an opendata driver implemented at the server. The method can further include the server retrieving document metadata from the opendata provider, building an internal model of the document metadata, and responding to a metadata request. A system for implementing the method and a non-transitory computer readable medium are also disclosed.