Multidimensional Database Transaction Tracking and Reporting
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Solution Overview
Problem
Current systems for transaction logging and data analysis are separate, with OLTP systems being inefficient for generating reports and OLAP systems having limited transactional capabilities, making it difficult to manage complex financial data and track transactions effectively.
Innovation Solution
Implementing transaction-oriented functions in a multidimensional database by adding dimensions to track balances and rules, allowing for the visualization of fund movements and rollback of transactions to identify rule impacts, enabling efficient transaction management and reporting.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If OLTP systems are used to store financial transactions in ledgers, then data entry and maintenance is easy, but generating complex reports is inefficient and time consuming
Solution Approach 1:
The patent segments the database into two separate systems: an OLTP ledger system for transaction storage and an OLAP cube system for analytical reporting. The ledger maintains simple tabular structure for easy data entry, while the cube pre-aggregates data for efficient complex report generation, resolving the contradiction between ease of data maintenance and report generation efficiency.
Solution Approach 2:
The patent introduces an intermediary process that automatically extracts data from the OLTP ledger and loads it into the OLAP cube. This mediator enables the ledger to maintain its simplicity for data entry while the cube handles complex reporting, allowing both requirements to coexist without performance degradation.
2Productivity
If OLAP systems are used to generate complex reports efficiently, then report generation is fast, but transactional capabilities are limited
Solution Approach 1:
The patent divides the system into two functional segments: the OLTP ledger for transactional operations and the OLAP cube for analytical reporting. Each segment is optimized for its specific function, with the ledger handling transactions and the cube handling complex reports, thereby achieving both efficient reporting and transactional capabilities.
Solution Approach 2:
The automated data extraction and loading process acts as an intermediary between the OLTP ledger and OLAP cube. This mediator ensures that transactional data is efficiently transferred to the cube for analysis while maintaining the transactional integrity of the original ledger system.
3Device complexity
If data is stored in relational database tables like ledgers, then data structure is simple, but complex queries become difficult or impossible
Solution Approach 1:
The patent transforms the two-dimensional tabular data structure of the ledger into a multi-dimensional cube structure. The cube adds multiple dimensions (time, account, department, etc.) to the data organization, enabling complex multi-dimensional queries and analyses that would be difficult in traditional relational tables while maintaining the simplicity of the source data structure.
4Reliability
If reports are executed each time information is needed from OLTP systems, then data is current, but processing time and resources are consumed
Solution Approach 1:
The patent performs preliminary action by automatically extracting and loading data from the OLTP ledger into the OLAP cube in advance. This pre-aggregation of data allows complex reports to be generated quickly from the cube without consuming resources to re-process the original transactional data, thereby reducing report execution time while maintaining data currency.
Data Source
AI summary
Systems and methods that enable transaction oriented functions for a multidimensional database are provided. The systems and methods store a plurality of transactions in a multidimensional database, generate a first dimension including respective balances resulting from each of the transactions, and generate a second dimension identifying respective rules corresponding to each of the transactions.