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Enhancement and Scaling of Arts Education Data Platform for Multi-Community Deployment
  1. case
  2. Enhancement and Scaling of Arts Education Data Platform for Multi-Community Deployment

Enhancement and Scaling of Arts Education Data Platform for Multi-Community Deployment

launchpadlab.com
Education
Non-profit

Identified Challenges in Arts Education Data Access and Platform Scalability

The organization faces inconsistent access to arts education data across different communities, with current systems experiencing performance bottlenecks. Users require streamlined search, filtering, and contextual data presentation to make informed decisions, while the platform needs modernization for better scalability and multi-region support.

About the Client

A regional arts education nonprofit organization seeking to improve data visibility, user experience, and scalability of their community arts education platform to support multiple regions and stakeholders.

Goals for Developing an Optimized, Scalable Arts Education Data Platform

  • Redesign and improve the user experience for searching and browsing arts education data, including maps and portals.
  • Implement advanced filtering, contextual data display, and improved search capabilities to reduce user effort and increase engagement.
  • Upgrade platform architecture for enhanced performance, scalability, and multi-region support to accommodate additional communities.
  • Develop data dashboards and reporting tools to facilitate easy data digestion and sharing via PDFs.
  • Establish a robust API-based architecture to enable seamless integration with external data sources.
  • Leverage scalable open source technologies like relational databases, search engines, and modern web frameworks.

Core Functional System Capabilities for Arts Education Data Platform

  • Interactive map and portal interface with streamlined search and filtering capabilities.
  • Contextually rich search results with both map and list views, providing detailed data points.
  • Data dashboards with visualizations, categorized data, and scoring metrics for schools and partners.
  • Automated PDF report generation based on collected data for easy sharing.
  • Multi-region (multi-tenancy) architecture supporting deployment to multiple communities.
  • API-driven design enabling integration with external and partner data sources.
  • Data storage leveraging relational databases and search engines for optimized read access and analytics.

Recommended Technologies and Architectural Approaches

Modern web frameworks such as ReactJS for frontend development
APIs built with scalable backend technologies
Open source relational database like PostgreSQL
Search optimization using Elasticsearch
Migration of monolithic architecture to modular, API-based architecture

Necessary Data and Service Integrations

  • External data sources for arts education, schools, and community partners
  • Existing portals and dashboards for data ingestion and display
  • PDF report generation services
  • Potential integrations with additional community or government datasets

Performance, Security, and Scalability Considerations

  • Platform must support large-scale data with high read performance, leveraging Elasticsearch for advanced search queries.
  • System architecture should facilitate easy scalability across multiple regions or communities.
  • Ensuring data security and compliance with relevant standards.
  • Responsive design for accessibility across devices.
  • Minimal latency with optimized performance for user workflows.

Anticipated Benefits and Business Outcomes of the Platform Enhancement

The revamped platform is expected to significantly improve user engagement by streamlining search and data access, provide richer contextual insights through dashboards, and support multi-community deployment, thereby attracting additional regional partners. These enhancements aim to increase data transparency and usage, ultimately supporting broader arts education initiatives across multiple regions, similar to the positive response observed from initial deployments.

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