Case Study

Driving Digital Transformation with Data-Driven Modernization

40%

Reduced app rendering time by 40%, delivering a smoother and faster user experience.

45%

Automated workflows reduced manual intervention by 45%, enhancing developer productivity and enabling faster feature rollouts.

INDUSTRY: Healthcare, Health Technology, Behavioral Health

SOLUTION: Advanced Data & AI Solutions

PLATFORM USE CASE: Delta Lake, data science, machine learning, ETL

CLOUD: AWS

HEAQUARTERS: McLean, Virginia

About the Client

A leading organization specializing in employee well-being and assistance programs has been addressing mental health and behavioral health challenges for over 30 years. Offering services like counseling, coaching, and advising, the company empowers organizations to enhance performance, satisfaction, and retention.

After a corporate acquisition, the organization identified a need to modernize its digital platform to reflect its new identity and improve operational efficiency, data security, and accessibility compliance. Partnering with DNAMIC, a leader in health informatics and AI-powered healthcare solutions, the organization leveraged Databricks on AWS to create a scalable, data-driven platform designed to transform service delivery and user experience.

The Challenge

Outdated Codebase and Dependencies:

A legacy React-based application caused slow data processing, increased latency, and security vulnerabilities.

Limited Testing and Documentation:

The lack of unit testing, functional testing, and API documentation reduced the platform’s reliability and scalability.

Accessibility Compliance Issues:

An audit revealed significant non-compliance with WCAG standards, impacting usability for users with disabilities.

Rebranding Requirements:

Post-acquisition, the platform required a full rebranding and seamless content migration to align with the new corporate identity.

The Approach

DNAMIC implemented a data-centric modernization strategy, leveraging Databricks on AWS to address the platform’s limitations and enhance its scalability, security, and accessibility. The key goals included:

Modernizing the codebase and data pipelines to improve performance and operational reliability.
Ensuring accessibility compliance and delivering a fully inclusive platform aligned with health technology standards.
Rebranding the platform to reflect the new corporate identity.
Enhancing operational efficiency through automation, testing, and streamlined workflows.

Technical Implementation

Data Pipeline Modernization:

Migrated the mobile application framework from React Native to Expo, optimizing workflows and reducing technical debt.
Updated backend dependencies to modern standards, ensuring reliability, scalability, and data integrity.

Rebranding and Content Realignment:

Upgraded the content management system from Drupal 8.9.2 to Drupal 10.2, facilitating seamless data migration and integration.
Redesigned the platform to reflect the new corporate branding and improve user experience (UX).

Accessibility and Security Enhancements:

Achieved 100% WCAG compliance, ensuring the platform is inclusive for users with disabilities.
Strengthened data security using Cognito authentication and robust encryption for API endpoints.

Performance Optimization:

Integrated Expo Application Services (EAS) to enable Over-the-Air (OTA) updates, simplifying the deployment of new features.
Conducted rigorous testing to optimize data processing workflows and improve system performance.

Operational Efficiency:

Implemented unit testing and comprehensive API documentation, reducing development time by 30% and improving maintainability.

01

There are two distinct front-end entry points the mobile user (via ReactNative) and the Web client (via Drupal) which acts as a admin portal.Two clouds are being used AWS and GCP currently.

02

Currently for the mobile user there are three authentication servicesbeing used Amazon Cognito and Firebase and Apple, but the profile isbeing stored in Firebase, while Cognito also handles notifications,passwords recovery, and other features.

03

The backend logic is handled using lambdas (which run NodeJs) tostore survey information coming from the mobile application, and alsosending notifications via the SES from AWS.

04

A multi-database approach is being used, using Firebase, DynamoDBand MySQL, which combines relational and non-relational (NoSQL)databases, and also an S3 bucket.

05

The EC2 instance, handles the server for Drupal which the currentversion is 8.9.2.

01

Data Ingestion: Data is brought into the Lakehouse from various sources (Notebooks, Scripts, Delta Live Tables, Auto Loader), ensuring all raw data is unified for processing.

02

Data Processing: Workloads run on Databricks Spark clusters with Apache Spark and MLflow, while Databricks Workflows automate the end-to-end pipeline.

03

Lakehouse Storage: A medallion architecture on Amazon S3 underpins the solution, with Unity Catalog enforcing governance and compliance.

04

Governance & Compliance: Unity Catalog manages data lineage, controls workflow/notebook permissions, and monitors compliance across the environment.

05

Data Serving: Insights are delivered via a ReactJS dashboard, ML models are deployed on Amazon SageMaker, and Databricks SQL Warehouse enables querying and analytics.

06

Security & Cost Management: IAM integration ensures user authorization, KMS handles secret management, git allows for code versioning and cost monitoring solutions track resource usage and spending.

Results and Impact

Performance Enhancements:

Reduced app rendering time by 40%, delivering a smoother and faster user experience.
Optimized workflows led to a 25% reduction in app size, improving load times.

Accessibility Compliance:

Achieved 100% accessibility compliance, creating an inclusive platform for all users.

Operational Efficiency Gains:

Automated workflows reduced manual intervention by 45%, enhancing developer productivity and enabling faster feature rollouts.

Scalability:

The platform now supports significantly larger data volumes while maintaining consistent performance and reliability.

Tech Stack

Mobile Framework: React Native, Expo
Backend: Node.js, Firebase
CMS: Drupal 8.9.2 → Drupal 10.2
Authentication: Cognito
Continuous Integration: Expo Application Services (EAS)

Future Vision

Advanced AI Capabilities:

Integrate predictive analytics to provide users with personalized insights and support.
Use machine learning to analyze trends in behavioral health, enabling data-driven service improvements.

Global Expansion:

Adapt the platform to meet international healthcare compliance standards and extend its reach to a global audience.

Enhanced Personalization:

Leverage health informatics to deliver tailored recommendations based on user preferences and historical data.

Collaborative Research:

Partner with academic institutions to analyze anonymized data for research in mental health and behavioral sciences.

Final Insights

By leveraging Databricks on AWS, DNAMIC transformed the organization’s digital platform into a modern, scalable, and data-driven solution. The project significantly improved performance, accessibility, and operational efficiency, aligning the platform with the organization’s mission of empowering mental and behavioral health. This case study highlights how advanced AI and data engineering can drive innovation and long-term success in the healthcare technology sector.

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Let’s Work Together

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Schedule a consultation with DNAMIC today to learn why healthcare and life sciences organizations
all across the US trust us to drive their AI and data transformation initiatives.

Let’s Talk Data: Chat with an Expert Now.

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Ready to Transform Your Data Into Actionable Insights?, Mariel Lozano will help you estimate your data project.

ml@dnamic.ai

Case Study

Driving Digital Transformation with Data-Driven Modernization

40%

45%

About the Client

The Challenge

Outdated Codebase and Dependencies:

Limited Testing and Documentation:

Accessibility Compliance Issues:

Rebranding Requirements:

The Approach

Technical Implementation

Data Pipeline Modernization:

Rebranding and Content Realignment:

Accessibility and Security Enhancements:

Performance Optimization:

Operational Efficiency:

01

02

03

04

05

01

02

03

04

05

06

Results and Impact

Performance Enhancements:

Accessibility Compliance:

Operational Efficiency Gains:

Scalability:

Tech Stack

Future Vision

Advanced AI Capabilities:

Global Expansion:

Enhanced Personalization:

Collaborative Research:

Final Insights

RELATED CONTENT

Genomics

Unlocking Genetic Insights

Neuroscience

Mapping the Mind

Let’s Work Together

Ready to Transform Your Data Into Actionable Insights?

Schedule a consultation with DNAMIC today to learn why healthcare and life sciences organizations all across the US trust us to drive their AI and data transformation initiatives. Let’s Talk Data: Chat with an Expert Now.

Let’s Work Together

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