Production Data Abstraction Layer for Cross-Database Analytics
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Solution Overview
Problem
Accessing production data across multiple databases is difficult due to the need for accessing local storages, which hinders the effective use of big data analysis tools and requires significant computational resources.
Innovation Solution
A system with an abstraction layer and a model interface that allows access to production data from multiple databases while minimizing computational resources by translating data requests and providing a harmonized data model for analytic workloads, using a microservice-based framework with containerized workloads and secure access management.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If production data is accessed from multiple local databases across different production sites, then the completeness and value of production data for analysis is improved, but the complexity of accessing and processing the data increases
Solution Approach 1:
The patent introduces an intermediary layer (abstraction layer) between the analysis tools and the multiple local databases. This intermediary handles data retrieval, transformation, and harmonization, allowing complete data access without requiring analysis tools to directly manage the complexity of multiple distributed database systems.
Solution Approach 2:
The patent creates a universal data access interface that can work with multiple different database systems and data formats. This universal interface handles various data types and structures from different production sites, providing a single point of access that works across all data sources without requiring separate access mechanisms for each database.
2Speed
If production data is copied to a centralized location for analysis, then the accessibility and speed of data retrieval is improved, but the computational resources and storage requirements increase
Solution Approach 1:
The patent extracts only the necessary data elements from the local databases and processes them at the source location where possible. Rather than copying entire datasets to a centralized location, the system extracts and processes specific production data locally, reducing the volume of data that needs to be transferred and stored centrally while maintaining fast access to the extracted information.
3Loss of information
If data from multiple production sites is accessed and processed, then the analytical insights and production improvements are improved, but the computational overhead and resource requirements increase
Solution Approach 1:
The patent segments the data processing workload into distinct components that can be executed at different locations. Data retrieval, transformation, and analysis are divided into separate operations that can run in parallel across multiple production sites, reducing the computational overhead at any single location while maintaining the ability to generate comprehensive analytical insights from all data sources.
Data Source
AI summary
The invention refers to a system (120) for accessing production data of production plants (130, 132, 134). The production data is stored on a plurality of databases (131, 133, 135). An abstraction layer (121) is adapted to access each of the databases for retrieving production data from a database and for providing the retrieved data for further processing. A model interface (122) is adapted to run analytic workloads requiring production data from the databases, and is further adapted to cause the abstraction layer to retrieve the required predetermined production data from the databases and to provide the retrieved required predetermined production data to the analytic workload running on the model interface. This allows for an access of production data of any type stored in a plurality of databases from anywhere and at any scale while requiring less computational resources.