Metadata Manager for Analytics Systems
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Solution Overview
Problem
Businesses face inefficiencies and high costs in processing and transforming data for reports due to manual updates of data schemas and transformation code, especially in multi-tenant systems, which require significant resources and time.
Innovation Solution
A metadata management system that automatically updates data schemas and transformation code in response to metadata changes, enabling quick and cost-effective data mapping across multiple tenants and applications.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual updates of data schemas and transformation code are performed, then data processing can be accomplished, but significant time and resources are required
Solution Approach 1:
The system enables self-service through automatic schema generation and transformation code creation. When metadata changes are detected, the system automatically generates updated schemas and transformation code without requiring manual administrator intervention, thereby eliminating time losses associated with manual updates while maintaining high productivity
Solution Approach 2:
The system performs preliminary actions by pre-defining schema templates and transformation rules that can be automatically applied when metadata changes occur. This preparation of update mechanisms in advance allows rapid schema updates without manual intervention, resolving the contradiction between fast processing and time consumption
2Adaptability or versatility
If manual schema changes are performed for each tenant, then data mapping can be updated, but quality assurance resources and time are required
Solution Approach 1:
The system implements universality through a centralized metadata management platform that serves multiple tenants simultaneously. A single schema template can be universally applied across all tenants, and automatic transformation code generation ensures consistent updates across the entire multi-tenant system, reducing both complexity and QA requirements while maintaining high adaptability
Solution Approach 2:
The system segments the multi-tenant environment into independent, manageable units while maintaining centralized control. Each tenant's schema updates can be independently managed through the automatic generation system, allowing flexible adaptation without increasing overall system complexity or requiring extensive QA resources for each individual tenant
3Adaptability or versatility
If data formats change frequently, then business needs are met, but manual schema updates become costly and time consuming
Solution Approach 1:
The automatic schema generation system performs self-service by detecting metadata changes and automatically generating updated schemas and transformation code. This eliminates the need for manual administrator intervention regardless of how frequently data formats change, maintaining high productivity while providing unlimited adaptability to format changes
Solution Approach 2:
The system implements feedback mechanisms that continuously monitor metadata changes and automatically trigger schema updates. When data format changes are detected, the system receives feedback about the change, automatically generates the necessary schema updates, and applies them without manual intervention, thereby maintaining high update efficiency despite frequent format changes
Data Source
AI summary
A metadata management system receives metadata changes and automatically updates a metadata architecture which maps the data. The metadata changes may be received through a simple user interface by a user or administrator. Once received, the system may automatically update schemas and data transformation code to process data according to the new data mapping preference. The system may handle metadata updates in a multi-tenant system having one or more applications per tenant, and may update data for a single tenant and 1 or more tenant applications in a multitenancy.