Healthcare Professional Data Engineering
Project overview
Backend data engineering for daily cleaning, database population, and visualization of doctor affiliations across life sciences.
Client information
H1 Insights is a leading New York-based healthcare data platform connecting life sciences companies, payors, providers, and patients.
Business challenge
To manage complex cases, our customer uses special technology solutions. Portfolio management is handled through modern, data-driven tools, and when cases go to litigation, these tools help H1 Insights make the whole process faster, more transparent, and harder for assessors to ignore.
H1 Insights required continuous data pipeline updates to track millions of medical professional profiles, clinical trials, and hospital affiliations.
The second challenge involves an increase in operational risk. With no clear visibility into problem areas, every investment decision was made amid significant uncertainty.
The final challenge was to define a clear roadmap for modernization across all layers (infrastructure, frontend, backend, and database) to guide future improvements.
Technical challenge
One of the main technical challenges was assessing a complex multi-layer system without causing disruption, while also prioritizing findings across architectural, operational, and organizational vulnerabilities. Additionally, it was essential to present findings in an actionable format, rather than simply cataloging historical changes.
Solution delivered
Aridian Technologies conducted a comprehensive engineering & development program to address all challenge areas. We built automated Python and PostgreSQL pipelines on Azure for daily data cleaning, validation, and visualization API feeds. Each finding was evaluated for severity and complexity, accompanied by actionable recommendations, and mapped into a phased modernization roadmap. This approach provided H1 Insights with a solid foundation for a structured, evidence-based remediation program.
Key deliverables
Team processes and project management review
- >Definition of team structure, roles, and responsibilities
- >Description of current processes and project management practices
- >Recommendations for improvement
Back end and database architecture review
- >Daily automated updates for millions of provider profiles
- >High data accuracy for life sciences research teams
- >Scalable Azure data pipeline with automated error handling
- >Custom analytics dashboards for enterprise clients
Front end review
- >Project structure assessment and recommendations for refactoring
- >UI/UX improvement recommendations
- >High-level security review and recommendations for improvement
Infrastructure review
- >Infrastructure patterns review and recommendations for improvement
- >Cloud resource utilization, security compliance, and cost optimization audit
- >Disaster recovery, backup protocols, and high-availability configuration review
Value delivered
Actionable modernization roadmap
Developed a clear, phased plan for system improvements, enabling the client to address technical debt and scale efficiently.
Risk reduction
Provided visibility into critical vulnerabilities, empowering the client to proactively manage operational and security risks.
Improved decision-making
Equipped stakeholders with evidence-based insights to support informed investment and resource allocation decisions.
Enhanced operational resilience
Ensured recommendations were sequenced to avoid production disruptions, resulting in a more robust and dependable platform.
Our tech stack
Healthcare Professional Data Engineering
Project overview
Backend data engineering for daily cleaning, database population, and visualization of doctor affiliations across life sciences.
Client information
H1 Insights is a leading New York-based healthcare data platform connecting life sciences companies, payors, providers, and patients.
Business challenge
H1 Insights required continuous data pipeline updates to track millions of medical professional profiles, clinical trials, and hospital affiliations.
Technical challenge
One of the main technical challenges was assessing a complex multi-layer system without causing disruption, while also prioritizing findings across architectural, operational, and organizational vulnerabilities.
Solution delivered
Aridian Technologies conducted a comprehensive engineering & development program to address all challenge areas. We built automated Python and PostgreSQL pipelines on Azure for daily data cleaning, validation, and visualization API feeds. Each finding was evaluated for severity and complexity, accompanied by actionable recommendations, and mapped into a phased modernization roadmap.
Key deliverables
Team processes and project management review
- >Definition of team structure, roles, and responsibilities
- >Description of current processes and project management practices
- >Recommendations for improvement
Back end and database architecture review
- >Daily automated updates for millions of provider profiles
- >High data accuracy for life sciences research teams
- >Scalable Azure data pipeline with automated error handling
- >Custom analytics dashboards for enterprise clients
Front end review
- >Project structure assessment and recommendations for refactoring
- >UI/UX improvement recommendations
- >High-level security review and recommendations for improvement
Infrastructure review
- >Infrastructure patterns review and recommendations for improvement
- >Cloud resource utilization, security compliance, and cost optimization audit
- >Disaster recovery, backup protocols, and high-availability configuration review
Value delivered
Actionable modernization roadmap
Developed a clear, phased plan for system improvements, enabling the client to address technical debt and scale efficiently.
Risk reduction
Provided visibility into critical vulnerabilities, empowering the client to proactively manage operational and security risks.
Improved decision-making
Equipped stakeholders with evidence-based insights to support informed investment and resource allocation decisions.
Enhanced operational resilience
Ensured recommendations were sequenced to avoid production disruptions, resulting in a more robust and dependable platform.
Our tech stack
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