Dynamic Stream Cube Materialization for Real-Time BI
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Solution Overview
Problem
Traditional Business Intelligence tools are inadequate for providing just-in-time analysis, as they are not designed to handle dynamic user requests and system changes, leading to inefficiencies in responding to real-time business events and data queries in multi-dimensional data streams.
Innovation Solution
A dynamic materialization strategy for stream cubes is implemented, where the materialization path is repeatedly determined based on a cost function and user requests, allowing for flexible cuboid materialization and adaptation to system conditions, such as data rates and memory availability, to ensure timely and relevant data analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If traditional BI tools are used for data analysis, then long-term decision planning is supported, but just-in-time analysis and real-time response to business events cannot be provided
Solution Approach 1:
The patent implements dynamic materialization of stream cubes where the materialization path is repeatedly determined based on current user requests and system conditions. This allows the system to adapt its data structure and computation strategy in real-time, transitioning from static traditional BI tools to a dynamic architecture that can provide just-in-time analysis while maintaining efficiency.
Solution Approach 2:
The system changes parameters such as materialization paths, aggregation levels, and computation strategies based on real-time system conditions including data rates and memory availability. This enables the system to optimize between different operational modes to achieve both fast response times and adaptability to varying user demands.
2Reliability
If full materialization of stream cube is implemented, then complete data availability is achieved, but system resource consumption and complexity increase
Solution Approach 1:
Instead of fully materializing the entire stream cube, the patent implements partial materialization along dynamically determined paths. This partial action approach provides sufficient data availability for current user requests while avoiding the resource consumption and complexity of complete materialization, achieving an optimal balance between reliability and device complexity.
Solution Approach 2:
The stream cube is segmented into multiple materialization paths, and only the relevant segments are materialized based on current user requests and system conditions. This segmentation allows the system to maintain data availability for needed queries while reducing overall system complexity and resource requirements by not materializing unnecessary portions.
3Ease of operation
If static materialization path is used, then system simplicity is maintained, but responsiveness to changing user demands and system conditions deteriorates
Solution Approach 1:
The patent transforms the static materialization path into a dynamic one that is repeatedly determined based on current user requests and system conditions. This dynamic approach maintains ease of operation through automated path selection while dramatically improving productivity by ensuring the materialization path always optimizes for current response efficiency requirements.
Data Source
AI summary
A computer readable storage medium comprises executable instructions to generate a stream cube to store data received from multiple data sources. A plurality of multi-dimensional data streams are generated to represent the received data. A materialization strategy is repeatedly determined for the stream cube. The stream cube is materialized according to the materialization strategy to record the multi-dimensional data streams.