USA
Belgium
France
UK
Australia
India
Singapore
Client Background
A Big Data Platform that centralizes different sources of data from payers, providers, clinicians etc.
Client Need
- Acquired more than 20 companies over the last decade. Multiple products with same use case running in silo environment and data being replicated in multiple location
- Required a centralized data storage required for data consumption/analysis
- Accelerate business growth by helping build new products, insights and enable AI and Machine Learning capabilities
Our Solution
- Designed and Developed Data Lake Platform using AWS S3 and Apache Spark to ingest and process millions of transactions from various data types like Claims, Payments, Eligibility, Clinical, Imaging, etc…
- Developed Pipeline Development Kit to create data pipelines with ease to quickly onboard tenant into the platform.
- Created Orchestration Development Kit using Apache Airflow for scheduling AWS EMR data pipelines
- Developed generic data pipelines for extracting and storing data that can be used by end users to search and retrieve their respective healthcare transactions using Elastic Search
Key Benefits
- Diverse and Ubiquitous Data amounting to 4 Peta Bytesof Cross Enterprise Financial, Operational, Clinical
- Cost Savings of $400K annually by opting to utilize S3 intelligent storage tier options and creating object’s life cycle rules
- Build Once – Use Multiple Framework – Operational Efficiency, Rapid Dev
- Faster On-Boarding – Reduced time to market, New Growth Opportunities
- Foundation for Integrated Products, Linked Cross Functional Data and enablement of Machine Learning and AI
- Authoritative source of Large Data Sets
Tools & Technologies
AWS
Amazon S3 Bucket
Spark
Apache Airflow
Kafka
Elasticsearch
PostgreSQL
Dev Ops
GotLab
HashiCorp Terraform
Docker
