Aggregate Data Maintenance via Additive Record Segmentation

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Solution Overview

Problem

Existing systems for maintaining aggregate data structures in business environments face inefficiencies due to frequent recalculations and high processing overhead, especially when transactional data changes frequently, leading to increased costs and reduced reporting performance.

Innovation Solution

A system that identifies changes to transactional data and automatically adds new aggregate records instead of updating existing ones, allowing for incremental maintenance and reorganization during low system usage, with the option to toggle modes based on data frequency and application requirements.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If the system updates existing aggregate records whenever transactional data changes, then the aggregate data remains current and accurate, but processing overhead and system costs increase significantly

Engineering Contradiction:

Improveaggregate data accuracyVSAvoidprocessing overhead

Core Design Contradiction:

ReliabilityVSDevice complexity

Solution Approach 1:

The patent segments the aggregate maintenance process into two distinct modes: additive mode for frequently changing data (adding records without updating) and update mode for stable data (updating existing records). This segmentation allows the system to optimize processing overhead based on data characteristics while maintaining aggregate accuracy through scheduled merges.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The system dynamically switches between additive and update modes based on the stability of transactional data. When data changes frequently, the system operates in additive mode to minimize processing overhead. When data stabilizes, it transitions to update mode to consolidate records and maintain accuracy, creating a dynamic adaptation mechanism.

Inventive Principle:

Principle #15Dynamics

2Measurement precision

If the system performs frequent recalculations of aggregate data, then reporting accuracy is maintained, but system performance and reporting speed deteriorate

Engineering Contradiction:

Improvereporting accuracyVSAvoidreporting performance

Core Design Contradiction:

Measurement precisionVSProductivity

Solution Approach 1:

The patent implements periodic action through scheduled merge operations that consolidate additive records into updated aggregate records at predetermined intervals. This periodic consolidation maintains reporting accuracy without requiring continuous recalculations, thereby preserving system performance between merge cycles.

Inventive Principle:

Principle #19Periodic action

Solution Approach 2:

The system performs preliminary actions by adding aggregate records incrementally as transactional data changes, rather than waiting for complete datasets before processing. This preliminary additive approach allows reporting to proceed with available data while maintaining the option to refine accuracy through later periodic merges.

Inventive Principle:

Principle #10Preliminary action

3Device complexity

If the system adds new aggregate records for every transactional data change, then processing overhead is reduced, but the aggregate data structure becomes fragmented and less efficient

Engineering Contradiction:

Improveprocessing overheadVSAvoiddata structure efficiency

Core Design Contradiction:

Device complexityVSStability of the object's composition

Solution Approach 1:

The patent applies merging by combining multiple additive aggregate records into a single updated record during scheduled merge operations. This merging process consolidates the fragmented data structure created by continuous additive operations, improving query efficiency and reducing storage overhead while preserving the low-processing-overhead benefits of additive mode.

Inventive Principle:

Principle #5Merging (Combining)

4Loss of time

If the system updates aggregate records in real-time, then data currency is maintained, but total cost of ownership increases due to frequent processing

Engineering Contradiction:

Improvedata currencyVSAvoidtotal cost of ownership

Core Design Contradiction:

Loss of timeVSLoss of energy

Solution Approach 1:

The system dynamically adjusts its operation mode based on data stability characteristics. For frequently changing transactional data, it operates in additive mode with minimal processing costs, accepting delayed currency. For stable data, it transitions to update mode to maintain currency. Scheduled merges periodically reconcile additive records to maintain overall data currency without continuous expensive updates.

Inventive Principle:

Principle #15Dynamics

Data Source

PatentUS8655923B2Simple aggregate mode for transactional data

Publication Date: 2014.02.18 SAP SE

AI summary

This disclosure provides various software and systems for efficiently maintaining aggregates. In one aspect, a system performing a computer implemented method identifies a first change to transactional data in a business application and automatically adds an aggregate record to an aggregate data structure based on the first change. The system then identifies a second change to the transactional data in the business application, the second change comprising an update to key figures associated with the first change. The system can prohibit an update to the aggregate record in the aggregate data structure based on the second change and automatically adds a second aggregate record to the aggregate data structure based on the second change to the transactional data, where the second aggregate record comprises the update to the key figures.