Reusable Transformation Templates for Data Warehouse Management
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Solution Overview
Problem
Existing data warehousing systems require separate transformation processes for each distinct native format from multiple data sources, making them inefficient and difficult to manage, especially when business rules or user interfaces need to be updated.
Innovation Solution
A system and method utilizing a library of reusable user transformations, where transformation templates are stored with unique identifiers, allowing instances to be instantiated and updated centrally, with changes propagated to all linked processes, and enabling impact analysis before implementation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If separate transformation processes are created for each distinct native format from multiple data sources, then each data source can be transformed into the common format of the data warehouse, but the system complexity and difficulty of management increase significantly
Solution Approach 1:
The patent implements a universal transformation template that can be instantiated multiple times to handle different data source formats. Instead of creating separate transformation processes for each data source, a single template with parameters allows one process to serve multiple functions across different native formats, thereby reducing overall system complexity while maintaining adaptability to multiple data sources.
Solution Approach 2:
The patent creates instances by copying a master transformation template. Each instance is a replicated copy of the template with specific parameter values assigned, allowing the same transformation logic to be reused across multiple data sources. This copying mechanism eliminates the need to manually create and manage separate transformation processes for each data source, significantly reducing management complexity.
2Adaptability or versatility
If separate transformation processes are maintained for each data source, then each process can be customized, but updates to business rules or user interfaces become difficult and time-consuming
Solution Approach 1:
The patent merges the common transformation logic into a single master template that is shared across all instances. When business rules or user interfaces need to be updated, changes are made to the master template once, and all instances automatically inherit these updates. This merging approach eliminates the need to update each transformation process separately, dramatically reducing maintenance time while preserving customization capability through instance-specific parameters.
Solution Approach 2:
The patent performs preliminary action by establishing the master template with all common transformation logic and structure before creating instances. This preliminary setup includes predefined parameters and transformation rules that can be easily updated later. By preparing the template in advance with updateable components, the system enables rapid propagation of changes to all instances without requiring time-consuming manual updates to each process.
3Productivity
If multiple separate transformation processes are used, then each process can handle its specific data source, but the overall system becomes inefficient and hard to manage
Solution Approach 1:
The patent creates a universal transformation template that can handle multiple data source formats through parameterization. This single template performs the function of multiple separate processes, improving productivity by eliminating redundant transformation logic while maintaining ease of management through centralized control. The template can be instantiated and configured for different data sources without creating separate processes, making the system both efficient and manageable.
Solution Approach 2:
The patent uses copying to create instances from the master template, allowing rapid deployment of transformation processes for multiple data sources. This copying mechanism improves productivity by automatically replicating proven transformation logic rather than creating processes from scratch, while simultaneously improving ease of management by maintaining a clear hierarchical relationship between the template and its instances that simplifies monitoring and control.
Data Source
AI summary
Data warehousing systems and methods are described herein. In one example methodology, a plurality of transformation templates are stored in a transformation library, each transformation template including software objects that describe how to transform extracted data prior to loading the data into the data warehouse. A unique identifier may be associated with each of the plurality of transformation templates. Using this unique identifier, an instance of at least one of the plurality of transformation templates may be instantiated into a data transformation process by mapping the software objects of the transformation template into the instance of the transform using code segments. The code segments of the data transformation process are then executed to transform and load the extracted data into the data warehouse.