Cloud Data Transform Logic Blocks for Multi-Tenant Integrity
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Solution Overview
Problem
Existing data transformations in cloud-based environments lack integrity checks, security, and validation, leading to potential inconsistencies and disruptions, especially in multi-tenant systems where changes must be uniformly propagated across distributed nodes.
Innovation Solution
Implementing data transform logic blocks with metadata-driven logic blocks that encapsulate transformation logic, using introspective tooling to identify dependencies and optimize parallel processing, and employing centralized reporting for monitoring.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If standard data transformations are used to update business data, then data can be modified to operate with modified applications, but the transformations execute without integrity checks, security, and validations, leading to potential data inconsistencies and disruptions
Solution Approach 1:
The patent introduces an intermediary validation layer between the data transformation logic and the target data structures. This intermediary component performs integrity checks, security validations, and dependency verification before transformations are applied, preventing inconsistent or disruptive changes while maintaining the adaptability of data transformations for modified applications
Solution Approach 2:
The system implements feedback mechanisms through validation rules and integrity checks that evaluate transformation outcomes before committing changes. If validations fail or dependencies are not met, the transformation is aborted, providing feedback that prevents data inconsistencies while allowing legitimate transformations to proceed
2Ease of manufacture
If data transformations are applied to single tables without centralized coordination, then transformations can be executed simply, but consistency across distributed nodes in multi-tenant systems cannot be ensured
Solution Approach 1:
The patent creates a universal transformation management system that handles multiple functions: local transformation execution, dependency resolution, consistency validation, and coordination across distributed nodes. This multi-functional framework maintains execution simplicity at the local level while ensuring global consistency across multi-tenant distributed systems
Solution Approach 2:
A centralized coordination intermediary is introduced that manages transformation propagation across distributed nodes. This intermediary coordinates transformation execution, ensures consistency requirements are met, and maintains stability across multi-tenant environments without complicating the local transformation execution logic
3Adaptability or versatility
If logic blocks are created to accommodate table changes, then data transformations can adapt to application modifications, but the complexity of ensuring uniform propagation across distributed nodes increases
Solution Approach 1:
The logic blocks are designed with self-service capabilities that automatically discover dependencies, validate transformation requirements, and propagate changes uniformly across distributed nodes. This self-service approach maintains adaptability to application changes while reducing system complexity by eliminating the need for external coordination for routine propagation tasks
4Ease of manufacture
If conventional data transformations are used without parallel processing optimization, then implementation is straightforward, but time spent performing data transformations increases
Solution Approach 1:
The patent segments data transformation operations into independent, parallelizable units that can be executed concurrently across multiple processors or nodes. Each segment maintains the straightforward implementation characteristics of conventional transformations while enabling parallel execution to improve overall transformation speed and productivity
Data Source
AI summary
The present technology pertains to systems and methods for executing data transformations within cloud-based service environments, such as SaaS platforms. The technology disclosed herein utilizes logic blocks to perform data transformations, incorporating all necessary logic and metadata to propagate changes in data structure. In an embodiment, a method includes receiving input that specifies a desired data transformation, creating a logic block to define the transformation, developing a transformation plan, and executing the logic block as per the plan to alter data stored in identified tables. Generating the transformation plan includes identifying the tables that contain the data to be transformed. The system described herein allows for efficient, consistent, and secure data transformations across multiple tenants in a distributed cloud service environment.