Cloud Analytics Engine Data Sharing via Metadata
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Solution Overview
Problem
Current database processing systems lack efficient methods for sharing and interacting with data from cloud-based analytics engines, particularly in accessing and modifying data presentations across different clients, and integrating data from third-party sources.
Innovation Solution
A system and method that utilizes a plugin to enable clients to interact with a cloud-based analytics engine by extracting and exporting data from third-party sources, applying machine learning models to identify entities and intent, and generating interactive data presentations that can be shared across clients, with metadata enabling seamless access and modification of data through a uniform resource identifier (URI), URL, or URN.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If data presentations are shared across clients through traditional methods, then data accessibility is improved, but data consistency and real-time updates deteriorate
Solution Approach 1:
The patent introduces a cloud-based analytics engine as an intermediary between multiple clients and the data source. This engine receives requests from any client, retrieves data from the centralized database, and returns consistent results to all clients. The engine acts as a mediator that ensures all clients access the same underlying data without directly sharing data between themselves, thus maintaining data consistency while enabling broad accessibility.
Solution Approach 2:
The patent extracts the data access logic from individual client applications and consolidates it into a separate cloud-based analytics engine. By taking out the data retrieval functionality from each client and centralizing it in the engine, the system ensures that all clients rely on the same data access pathway, preventing data inconsistency while maintaining ease of access for all users.
2Productivity
If cloud-based analytics engine is used for data processing, then data processing capability is improved, but system complexity worsens
Solution Approach 1:
The cloud-based analytics engine is designed as a universal system that handles multiple functions: data retrieval from the database, data processing and analysis, generation of data presentations, and serving multiple clients simultaneously. By consolidating these diverse functions into a single multi-functional engine, the system improves overall data processing capability while avoiding the complexity of having separate specialized systems for each function.
Solution Approach 2:
The patent merges the database access layer, data processing layer, and client interface layer into a single cloud-based analytics engine. This consolidation combines multiple previously separate components into one unified system, enhancing data processing capability through integrated operations while reducing the apparent system complexity by eliminating the need for clients to directly manage multiple separate components.
3Ease of operation
If metadata is used to enable client access to cloud-based analytics engine, then data accessibility is improved, but information security worsens
Solution Approach 1:
The analytics engine serves as an intermediary that handles all authentication and authorization requests. Clients provide metadata (such as user credentials or access tokens) to the engine, which then verifies the metadata against stored authentication information and grants or denies access accordingly. This intermediary approach enables easy client access through metadata while maintaining security by centralizing authentication logic and preventing direct access to the database.
Solution Approach 2:
The system implements self-service authentication where the analytics engine automatically validates client metadata and manages access control without requiring manual intervention. The engine independently verifies client credentials, determines appropriate access levels, and enforces security policies, thus improving accessibility through automated processes while maintaining security through consistent enforcement of access rules.
Data Source
AI summary
A method for sharing access to data from a cloud-based analytics engine may include receiving, at a first client, a message from a second client. The message may include an image of a data presentation and metadata associated with the data presentation. The first client may respond to a selection of the image of the data presentation by accessing the cloud-based analytics engine to retrieve, based on the metadata associated with the data presentation, data associated with the data presentation. The data presentation may generated for display at the first client based on the data retrieved from the cloud-based analytics engine. The data presentation displayed at the first client may be interactive to enable an application of one or more modifications to the data presentation displayed at the first client. Related systems and articles of manufacture are also provided.