Analyst Workspace Containers for Reusable Multi-Tenant Data Relationships
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Solution Overview
Problem
Multi-tenant systems lack mechanisms for analysts to develop and share insights efficiently, with data often scattered and disconnected, and existing systems do not support reuse of analytics components or workspaces at an individual analyst level.
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 data is centralized in a unified data analytics platform, then data accessibility and collaboration are improved, but system complexity and data organization challenges increase
Solution Approach 1:
The patent segments the unified data analytics platform into multiple workspaces, each serving specific analytical purposes. Workspaces divide the large centralized data environment into smaller, manageable units that can be independently organized and accessed, reducing the perceived complexity while maintaining centralized data accessibility.
Solution Approach 2:
The patent introduces workspace containers as intermediary structures between the centralized data platform and individual analysts. These workspaces act as mediators that organize data, components, and insights, simplifying the interaction between users and the complex underlying data infrastructure.
2Productivity
If workspaces are created for individual analysts, then analyst productivity and insight sharing are improved, but data organization complexity increases
Solution Approach 1:
The patent creates workspaces with universal structures that can serve multiple analysts and multiple analytical purposes. Each workspace follows a standardized template containing common components like data connections, transformations, and visualization elements, allowing reuse across different analytical contexts while maintaining consistent organization.
Solution Approach 2:
The patent pre-configures workspace templates with essential components and structures before analysts begin their work. By providing pre-established frameworks for data organization, connections, and insights, analysts can immediately begin productive work without needing to create organizational structures from scratch, reducing the complexity burden.
3Productivity
If analytics components are made reusable across workspaces, then efficiency is improved, but component management complexity increases
Solution Approach 1:
The patent enables analysts to copy analytics components (such as data connections, transformations, and visualizations) between workspaces. This copying mechanism allows proven analytical components to be reused across different workspaces and analysts, improving efficiency while the standardized workspace structure helps manage the complexity of component proliferation.
Data Source
AI summary
A multi-tenant system receives a request to generate a first workspace according to at least a subset of tenant data stored in a plurality of data spaces. The system determines a collection of components of the first workspace and determines a respective data and/or metadata source for each component of the collection of components. The respective data and/or metadata source corresponds to a data space of the plurality of data spaces. The system receives, via the plurality of data spaces, data and/or metadata for each component of the collection of components and stores the data and/or metadata of the first workspace to each component. The system also stores, in a multi-tenant junction table, relationships between the first workspace, the collection of components of the first workspace, and respective objects from the plurality of data spaces.