Mobile Analytics Engine Metadata Query Adaptation
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Solution Overview
Problem
Mobile business applications face challenges due to limited data transfer rates, processing power, and unpredictable connectivity, which hinder their ability to provide analytical features comparable to those on enterprise computing platforms.
Innovation Solution
A mobile analytics engine implements a business analytics model with metadata models to dynamically modify query or report content for optimized execution under resource constraints, using a metadata repository to provide a generic interface for diverse mobile business analytics applications and adjust queries based on data transfer capacity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If mobile devices use enterprise-level analytical features, then analytical capability is improved, but device resource consumption increases
Solution Approach 1:
The patent segments analytical processing into two parts: complex analytical operations are performed on the backend server, while the mobile device only handles data retrieval and presentation. This segmentation allows enterprise-level analytical features to be available on mobile devices without consuming significant local resources, as the heavy processing occurs remotely on the server infrastructure.
2Speed
If data transfer rate is increased for analytics, then query execution speed is improved, but network bandwidth consumption increases
Solution Approach 1:
The patent implements preliminary action by pre-processing and aggregating analytical data on the backend server before it is transferred to the mobile device. Queries are optimized at the server level to retrieve only necessary aggregated results rather than raw data, which speeds up query execution while minimizing the amount of data that needs to be transferred over the network.
3Power
If processing power is increased on mobile device, then local analytics performance is improved, but device hardware requirements increase
Solution Approach 1:
The patent introduces a backend server as an intermediary between the mobile device and the analytical processing infrastructure. The server acts as a mediator that handles all complex analytical computations, allowing mobile devices to access enterprise-level analytics capabilities without needing enhanced local processing power or sophisticated hardware.
4Measurement precision
If connectivity is made more reliable for analytics, then data accuracy is improved, but connection stability requirements increase
Solution Approach 1:
The patent applies preliminary action by pre-computing and caching analytical results on the backend server before they are needed by the mobile device. This approach ensures that when data is transferred, it is already processed and accurate, reducing the need for continuous stable connections during critical data transfer moments and improving data accuracy without imposing strict connection stability requirements.
Data Source
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AI summary
A mobile computing platform for a mobile device, which has an interface for a remote connection to a backend server, includes a mobile analytics engine. The mobile analytics engine is configured to implement a mobile analytics model, which defines data, query and report structures for analytics of business data stored on the backend server. The mobile analytics engine uses model metadata to provide a generic reporting and analytics interface to support diverse mobile business analytics applications.