This project centers on a data management and visualization platform built to support the full administrative lifecycle of analytics configuration—from data ingestion to secure, role-based dashboard access.

The platform enables:

• Integration of SQL and API data sources

• Definition of validation, transformation, and summarization logic

• Configuration of interactive dashboards

• Controlled access through role-based assignment

The system is structured to support complex technical configuration while maintaining clarity, auditability, and accessibility in large-scale organizational environments.

Problem

Many organizations depend on manual reports, static dashboards, and ad-hoc queries, which introduces systemic issues:

• Data remains fragmented across multiple sources

• Reporting changes require engineering involvement

• Raw metrics are difficult to interpret without domain expertise

• Role-based access is inconsistently enforced

• Existing tools lack keyboard and screen-reader accessibility

A centralized, self-service analytics system with built-in governance was required.

Solution

The platform is organized around a lifecycle-driven configuration model that guides administrators through a clear, dependency-aware workflow:

1. Data ingestion and optional composition

2. Parameter and constraint definition

3. Data transformation and summarization

4. Visualization and interaction behavior

5. Role-based assignment and access control

The UI applies progressive disclosure, validation-first interaction patterns, and embedded access governance to reduce configuration errors while supporting advanced use cases.

Key Capabilities

• Multi-source data ingestion (SQL / API) with optional joins

• Expression-based validation for dashboard inputs

• Field value mapping for readable, decision-ready insights

• Interactive, table-based visualizations with drill-down behavior

• Role- and entity-level access control

• WCAG 2.1 AA–aligned keyboard and screen-reader support

Outcomes

• Reduced operational dependency on engineering for reporting changes

• Faster dashboard configuration and iteration cycles

• Improved interpretability of analytical data

• Consistent enforcement of access and compliance rules

• Increased accessibility across administrative workflows

Key Learnings

• Complex systems benefit from clear mental models, not reduced capability

• Early validation prevents downstream configuration failure

• Governance and compliance are most effective when enforced through UX

• Accessibility must extend beyond end-user views into administrative tooling

Note on confidentiality:
Certain implementation details and interface screens have been intentionally abstracted to respect confidentiality obligations. The material shown focuses on system design, workflow structure, and accessibility principles. Additional context and design rationale can be shared through appropriate professional channels if needed.