Dynamic Data Transformation System Governance Tracking
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Solution Overview
Problem
Conventional systems fail to efficiently and accurately transform data and track data governance in large enterprise organizations, making it difficult to provide consistent and accurate information for internal and regulatory purposes.
Innovation Solution
A dynamic data transformation system that ingests data from various sources, executes data governance functions, performs transformations, and captures data lineage information, enabling in-memory processing and efficient data publication while ensuring data quality and control throughout the process.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional systems process data through multiple transformation stages, then data can be transformed and published to downstream systems, but data governance information becomes difficult to track and maintain accuracy
Solution Approach 1:
The system performs preliminary action by capturing data governance information at the source system before data leaves the originating database. This includes capturing metadata, data quality attributes, and lineage information during the data generation phase, rather than attempting to track it through subsequent transformation stages. This preliminary capture ensures accuracy is established early and reduces the complexity of tracking through multiple systems.
Solution Approach 2:
The system introduces an intermediary component that acts as a bridge between the source system and downstream systems. This intermediary captures and standardizes data governance information in a uniform format, allowing it to be transported and maintained across multiple transformation stages without requiring complex tracking mechanisms at each stage. The intermediary serves as a single point of control for data governance information.
2Adaptability or versatility
If data is transformed dynamically through multiple processing stages, then data can be adapted to different downstream requirements, but the effort and code modifications required increase significantly
Solution Approach 1:
The system implements a universal data governance information structure that can serve multiple downstream systems with different requirements. By capturing comprehensive governance information once at the source in a standardized format, the same data can be adapted to various downstream targets without requiring separate tracking or transformation logic for each destination. This multi-functional approach reduces implementation effort while maintaining high adaptability.
Solution Approach 2:
The system enables dynamic data transformation by allowing parameters such as data format, quality thresholds, and lineage representation to be changed based on downstream requirements. The core data governance information remains consistent, but its presentation and specific attributes can be adjusted through parameter changes rather than code modifications, facilitating easy adaptation to different systems.
3Loss of information
If comprehensive data governance tracking is implemented across all data stages, then complete data lineage information can be captured, but processing time and system overhead increase
Solution Approach 1:
The system extracts data governance information as a separate, independent component from the main data transformation process. By capturing metadata, lineage, and quality attributes as distinct data structures that travel parallel to the actual data, the system achieves complete information tracking without adding significant overhead to the core data processing pipeline. The governance information is captured once and transported efficiently alongside the data.
Data Source
AI summary
Systems for dynamically transforming data are provided. Database data may be received and ingested into a system. Ingesting the data may include executing one or more first data governance functions, such as data quality evaluation functions, data controls, and the like. The ingested data may then be output for further processing as first processed data and first data governance information may be captured and stored. The first processed data may be processed to execute one or more data transformations. Data transformations may include calculations, formatting, derivations, and the like. In some arrangements, second data governance functions may be executed on the transformed data. The transformed data may then be output as second processed data. The system may capture second data governance information as the data is transformed. The second processed data may then be published to one or more downstream databases for use in one or more applications executed by an entity.