Isolated Analyst Workspaces for Secure Multi-Tenant Data Reuse
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Solution Overview
Problem
Multi-tenant systems lack the capability to support reusability of analytics components and workspace environments where analysts can develop and share insights, with data silos preventing efficient collaboration and decision-making.
Innovation Solution
Implementing workspace containers optimized for individual analysts, allowing data and metadata reuse across workspaces, and enabling personal spaces for analysts to develop insights that can be shared or promoted to a governed organization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a multi-tenant system centralizes data for a tenant organization from various sources into a single platform, then data accessibility and collaboration are improved, but data silos and security control are worsened
Solution Approach 1:
The patent segments the multi-tenant system into distinct workspace containers, each isolated from others but functioning independently. Each workspace acts as a self-contained environment that can access and process data from various sources without creating silos, as the segmentation is managed at the container level rather than creating isolated data silos. This resolves the contradiction by providing structured accessibility while maintaining organizational integrity.
Solution Approach 2:
The workspace container serves as an intermediary layer between the centralized data platform and individual analysts. This intermediary enables controlled access to data from various sources while maintaining security boundaries and preventing unauthorized access. The container mediates between the need for broad data accessibility and the need for security control, allowing analysts to work with diverse data sources without compromising system security.
2Productivity
If workspace containers are implemented for individual analysts, then analyst productivity and insight development are improved, but system complexity and administration overhead are worsened
Solution Approach 1:
The workspace container is designed as a universal, multi-functional unit that can be deployed for any analyst while providing consistent capabilities. Each container serves multiple functions: data access, analysis, visualization, and collaboration. This universality reduces system complexity by using a standardized template rather than creating custom environments for each analyst, thereby improving productivity without proportionally increasing administrative overhead.
Solution Approach 2:
The workspace container employs a nested structure where multiple functional components are contained within a single unified container. This nesting allows complex analyst environments to be packaged as manageable units that can be easily provisioned, configured, and administered. The nested architecture improves productivity by providing comprehensive functionality while reducing system complexity through hierarchical organization and standardized interfaces.
3Productivity
If data is centralized in a single platform, then decision-making efficiency is improved, but data security and access control are worsened
Solution Approach 1:
The system applies local quality by granting different access permissions and data visibility to different workspace containers based on specific analyst needs and organizational policies. Each workspace has tailored access controls that provide the necessary data for decision-making while restricting access to sensitive information. This localized approach to security maintains centralized data architecture for efficiency while implementing granular access control for security.
Solution Approach 2:
The workspace container acts as an intermediary that enables secure access to centralized data. It mediates between the centralized data platform and individual analysts, providing controlled access to the data needed for efficient decision-making while enforcing security policies. The container ensures that analysts can access relevant data without compromising overall data security, thus resolving the contradiction between decision-making efficiency and data security.
Data Source
AI summary
A multi-tenant system stores tenant data for a tenant in a data space. The system receives a request from a user to generate an isolated workspace according to the tenant data stored in the data space. The user has non-administrative access control with respect to the data space of the multi-tenant system. The system, in accordance with receiving the request, provisions an isolated organization to the user, including establishing administrative access control for the user with respect to the isolated organization while maintaining the non-administrative access control for the user with respect to the data space. The computer system replicates at least a subset of metadata from the data space to the isolated organization. The subset of metadata is accessible to the user in the data space and describes a corresponding subset of data. The system stores, in the isolated organization, all components created in the isolated organization.