Data Warehouse Model Federation via Semantic Interface
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Solution Overview
Problem
Existing data warehouse systems face challenges in interoperability, as clients need to interact with proprietary interfaces of different data warehouses to access and manage semantically enriched models, leading to increased complexity and restricted access.
Innovation Solution
A method for data warehouse model federation that allows converting a semantically enriched model from a source data warehouse to a target data warehouse, providing access to the associated data and security policies, and deploying the transformed model, thereby enabling seamless integration and reuse across different data warehouse systems.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If clients interact with proprietary interfaces of different data warehouses to access semantically enriched models, then access to models is enabled, but system complexity increases
Solution Approach 1:
The patent introduces a federation interface as an intermediary layer between clients and multiple data warehouse proprietary interfaces. This mediator translates and harmonizes interactions with different proprietary interfaces, enabling clients to access semantically enriched models across multiple data warehouses without directly dealing with each proprietary interface's complexity.
Solution Approach 2:
The federation interface provides a universal access mechanism that works across multiple data warehouse systems with different proprietary interfaces. Instead of requiring separate client implementations for each data warehouse, the universal federation interface handles diverse interface requirements, reducing overall system complexity while maintaining broad access capability.
2Adaptability or versatility
If semantically enriched models are converted between different data warehouse interfaces, then model availability increases, but conversion complexity increases
Solution Approach 1:
The patent creates copies of semantically enriched models when converting them between different data warehouse interfaces. Instead of complex real-time transformations, the system generates and stores model copies in target data warehouse formats, enabling efficient retrieval and reducing conversion complexity while maintaining model availability across multiple systems.
Solution Approach 2:
The conversion process performs preliminary actions by pre-processing and pre-converting models to target interface formats before deployment. This advance preparation reduces the complexity of runtime conversions and enables smoother model availability across different data warehouse systems.
3Speed
If data is replicated across data warehouses for model conversion, then access speed improves, but data redundancy increases
Solution Approach 1:
The patent applies local quality by replicating only the specific data portions required for semantically enriched models in each data warehouse, rather than performing full data replication. This selective local replication improves access speed for model operations while minimizing unnecessary data redundancy across the distributed system.
Data Source
AI summary
The present disclosure describes methods, systems, and computer program products for providing data warehouse model federation. One computer-implemented method includes receiving a request to transform a first semantically enriched model to a second semantically enriched model, wherein the first semantically enriched model operates in a first data warehouse and the second semantically enriched model operates in a second data warehouse; identifying a set of data associated with the first semantically enriched model, wherein the set of data is stored in the first data warehouse; providing access to the set of data associated with the first semantically enriched model from the second data warehouse; creating the second semantically enriched model based on the first semantically enriched model using an interface of the second data warehouse; and deploying the second semantically enriched model in the second data warehouse.