Development of a Customizable Embedded Analytics Platform with Multitenancy for Healthcare Data Management

The client faces limitations in existing analytics platforms which lack sufficient customization options for end-users, hinder multitenancy support, and present challenges in secure data synchronization. These issues restrict the ability to deliver tailored, secure insights to healthcare organizations and limit operational efficiency and data-driven decision-making.

A mid to large-scale healthcare analytics provider aiming to deliver advanced, customizable data visualization and insights to healthcare organizations through a SaaS platform.

• Expand end-user capabilities to customize dashboards and interfaces based on specific organizational needs.
• Implement multitenancy support within the analytics platform, ensuring data and content separation for multiple healthcare clients.
• Develop secure data synchronization mechanisms between client data sources and the visualization platform.
• Automate daily data refresh processes to keep analytics dashboards up-to-date with latest data.
• Enable processing and management of large, complex healthcare datasets, including clinical, financial, and patient satisfaction metrics, to facilitate in-depth analysis.
• Enhance user experience through embedded, flexible visualization components, improving accessibility and usability.

• Customizable visualization components embedded within dashboards to enable flexible data review and crossfiltering.
• Support for multitenant architecture with separate content and data access controls per organization.
• Secure user and client data synchronization with dedicated authorization and data storage mechanisms.
• Automated nightly schedule for updating dashboards with the latest data extracts.
• Robust data management to process billion-row scale datasets across clinical, financial, and patient satisfaction metrics.
• Data filtering and transformation pipelines to prepare large healthcare data for visualization, removing irrelevant information, and structuring it for optimal performance.

• External data sources providing clinical, financial, and patient satisfaction data
• Authorization and authentication services for secure user access
• Database systems for structured data storage and retrieval
• Scheduling systems for nightly data refresh automation

• Scalability to handle datasets with over one billion rows per client
• High performance to support real-time and near real-time data refreshes
• Secure data handling with isolated tenant data spaces and encryption standards
• Reliability and availability with minimal downtime for scheduled updates
• User-friendly interfaces with high customization flexibility

The implementation of advanced customization, multitenancy, and automated data management is expected to significantly improve analytical capabilities for healthcare organizations, leading to more tailored insights and operational efficiency. This will facilitate better performance measurement, enhance patient satisfaction, and position the platform as a top-tier solution in the healthcare data management market.