Automated Schema Generation for Business Analytics Data Provisioning
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Solution Overview
Problem
The process of moving data from operational data stores to enterprise data warehouses and OLAP storage areas is time-consuming and expensive, requiring substantial upfront investment to evaluate current and future requirements for business analytics information provisioning.
Innovation Solution
A system dynamically generates schema terms by matching input data query requirements to industry terms, creating an associative map and query to retrieve and load data into storage areas, thereby streamlining the data provisioning process.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If data movement from operational data stores to enterprise data warehouses and OLAP storage areas is programmed by database programmers, then data provisioning can be accomplished, but the process becomes time-consuming and expensive
Solution Approach 1:
The system enables self-service data provisioning by automatically generating schema terms, associative maps, and queries without requiring database programmers. The automated system evaluates data requirements, creates provisioning schemas, and executes data movement tasks independently, eliminating the need for manual programming and significantly reducing both time and cost
Solution Approach 2:
The invention changes the parameters of the data provisioning process by transitioning from manual programming to automated generation. The system dynamically adjusts provisioning parameters based on evaluated requirements, automatically modifying schema definitions, associative map structures, and query configurations to optimize data movement efficiency
2Reliability
If substantial money and up-front time are invested to evaluate current and future requirements, then accurate business analytics information provisioning can be achieved, but the cost and time investment becomes excessive
Solution Approach 1:
The system performs preliminary evaluation of data requirements automatically before data provisioning begins. By pre-assessing both current and future data needs through automated analysis, the system prepares appropriate schemas and configurations in advance, ensuring reliable information provisioning without requiring excessive manual time investment in requirement evaluation
Solution Approach 2:
The invention implements feedback mechanisms that continuously monitor and evaluate data provisioning effectiveness. The system uses this feedback to automatically adjust and refine its provisioning strategies, improving accuracy over time while reducing the need for extensive upfront requirement evaluation through iterative optimization
Data Source
AI summary
An approach is provided in which a system creates schema terms based upon matching input data query requirements to industry terms. In turn, the system generates a query and an associative map, which includes data organized according to the schema terms. The system executes the query, which retrieves the data from the associative map and loads the data into one or more storage areas.