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Modernizing Patient-Data Pipelines for United Healthcare

Impact Delivered

  • 80% Reduction in time-to-market
  • 70% Increase in user adoption
  • 60% Improvement in collaboration
  • 15% Overall cost reduction
  • The Customer

    The Customer

    A leading US healthcare insurer (United Healthcare) needing timely insights from massive EDI/patient data while enabling analysts/engineers with self-serve advanced analytics.

  • The Challenge

    The Challenge

    3D-Priniting-Challenges-Img.jpg
    • Complex, siloed, manual processes with limited automation and governance
    • Inadequate data-quality assessment limiting trust and actionability
    • Collaboration bottlenecks without a single pane of glass
    • Need to scale from local to cloud to accelerate delivery
  • The Solution

    The Solution

    the-solution-img_nextiva.jpg

    Deploy secure, governed data/ML workflows at enterprise scale on AWS:

    • Rapidly connect to S3, DynamoDB, Redshift, RDS; orchestrate on Airflow; scale with EMR
    • Provide reusable ETL/ML patterns and collaborative project/workflow sharing
    • Embed extensive data-quality checks; enable quick analytical apps and reporting
  • Solution Components

    Solution Components

    EMR; S3; DynamoDB; Redshift; RDS; Airflow; AWS Data Lake

  • The Results

    The Results

    • Faster, trustworthy analytics for EDI/patient data
    • Streamlined cross-team execution and reuse
    • Scalable pipelines supporting 100+ daily jobs
    • Tangible reduction in cost and lead time

Impact Delivered

  • 80% Reduction in time-to-market
  • 70% Increase in user adoption
  • 60% Improvement in collaboration
  • 15% Overall cost reduction

The Customer

A leading US healthcare insurer (United Healthcare) needing timely insights from massive EDI/patient data while enabling analysts/engineers with self-serve advanced analytics.

The Challenge

3D-Priniting-Challenges-Img.jpg
  • Complex, siloed, manual processes with limited automation and governance
  • Inadequate data-quality assessment limiting trust and actionability
  • Collaboration bottlenecks without a single pane of glass
  • Need to scale from local to cloud to accelerate delivery

The Solution

the-solution-img_nextiva.jpg

Deploy secure, governed data/ML workflows at enterprise scale on AWS:

  • Rapidly connect to S3, DynamoDB, Redshift, RDS; orchestrate on Airflow; scale with EMR
  • Provide reusable ETL/ML patterns and collaborative project/workflow sharing
  • Embed extensive data-quality checks; enable quick analytical apps and reporting

Solution Components

EMR; S3; DynamoDB; Redshift; RDS; Airflow; AWS Data Lake

The Results

  • Faster, trustworthy analytics for EDI/patient data
  • Streamlined cross-team execution and reuse
  • Scalable pipelines supporting 100+ daily jobs
  • Tangible reduction in cost and lead time
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