Product Introduction
Definition: Basedash View-only members is a secure role-based access control (RBAC) feature within the Basedash AI analytics platform. Categorized under Business Intelligence (BI) user management and embedded analytics governance, this capability allows organizations to provision read-only licenses to internal stakeholders, external clients, or entire enterprise departments without exposing underlying database write privileges or configuration panels.
Core Value Proposition: This feature exists to bridge the gap between technical data teams and non-technical stakeholders by democratizing data visibility securely. By implementing Basedash View-only members, organizations can share critical business metrics, automated reports, and interactive dashboards widely across teams while strictly preventing unauthorized edits, accidental schema modifications, or unbounded AI chat querying. It solves the enterprise dilemma of balancing broad data transparency with strict security and governance.
Main Features
Interactive Dashboard & Chart Execution: View-only members are granted permission to interact dynamically with shared analytical assets. This includes opening curated dashboards, executing pre-saved charts, utilizing global dashboard filters, performing data drilldowns, and exporting results into standard file formats like CSV or Excel without needing direct SQL knowledge or query-building capabilities.
Flexible Multi-Channel Role Assignment: Administrators can assign the view-only role granularly across multiple access points depending on the deployment architecture. Roles can be designated directly within the invite dialog, adjusted via member settings, automated programmatically using the Basedash REST API, or securely authenticated dynamically through embedded sign-in tokens utilizing JWT (JSON Web Tokens) SSO.
Restricted Administrative & AI Boundaries: To maintain enterprise data hygiene, view-only accounts are programmatically restricted from creating, deleting, or modifying dashboards, metrics, and data models. Furthermore, they are blocked from executing background automations, triggering automated AI insights, or engaging directly with the native Basedash AI chat assistant to consume conversational LLM token quotas or query raw ungoverned database tables.
Problems Solved
Pain Point: Accidental data corruption, unauthorized query execution, and inflated software licensing costs caused by giving full-edit access to casual business consumers who only require visibility into pre-compiled reports.
Target Audience: Enterprise department heads, client-facing account managers, external clients, security compliance officers, and finance stakeholders who need real-time data access but lack technical data modeling expertise or authorization to alter core analytics infrastructure.
Use Cases: Essential for SaaS companies embedding analytics portals for enterprise clients where end-users must filter shipping metrics or financial performance without editing workspace schema; vital for operational reviews where department leads need to drill down into pre-built revenue dashboards without altering governed metric definitions.
Unique Advantages
Strengths & Limitations (Pros & Cons):
- Strengths: Exceptional security isolation, frictionless deployment via API or embed tokens, zero training required for end-users, and significant cost savings compared to provisioning full-seat BI licenses for casual readers.
- Limitations: Because view-only members cannot chat with the AI assistant or modify existing models, custom ad-hoc questions outside the scope of pre-saved charts still require escalation to data-authorized team members.
Key Alternatives & Differentiation:
- Traditional BI Tools (e.g., Tableau, Looker): Traditional platforms often handle viewer tiers via complex, rigid viewer licensing models that require extensive server configuration. Basedash streamlines this through modern API-driven token generation and instant React-based embedding.
- Open-Source BI (e.g., Metabase): While Metabase offers basic read-only group permissions, Basedash integrates view-only access natively with AI-generated semantic layers and automated audit logs, ensuring that even non-editing consumers benefit from governed metrics and source attribution.
Frequently Asked Questions (FAQ)
Can Basedash view-only members run custom SQL queries? No. View-only members cannot write, edit, or execute custom SQL statements. They are restricted to running pre-saved charts, applying built-in dashboard filters, and performing authorized drilldowns on existing curated data.
How do I provision a view-only member in Basedash? You can assign the view-only role during user invitation via the dashboard UI, update existing permissions in member settings, automate provisioning through the Basedash API, or pass appropriate claims via embed sign-in tokens.
Do view-only members consume AI chat credits? No. Because view-only members are blocked from using the AI chat interface and executing raw AI-generated queries, their usage does not consume interactive LLM conversational quotas.
Can view-only members export data from dashboards? Yes. Stakeholders with view-only access retain the ability to export result sets from saved charts and dashboards for offline analysis, depending on workspace-level security policies.
