Δ
Healthcare
Web Platform
Python, Azure Data Factory, Azure Databricks
Our client, a prominent healthcare performance improvement company, offers SaaS solutions for acute and ambulatory care providers and academic medical centers. Collaborating with diverse healthcare entities, the company offers services in analytics, contract management, operational oversight, and supply chain management to enhance the delivery of high-value care, aligning cost, quality, and market performance.
The client’s on-premise solutions merge supply and clinical data for healthcare providers and insurance companies. This data covers diagnoses, procedures, medications, and medical equipment. It enables executives to enhance patient outcomes and reduce operational costs.
Their existing solutions were hard to maintain and required huge investments of resources to support. The client turned to NIX as a trusted vendor renowned for our extensive expertise in cloud services. The goal was to transition their on-premise system to a more scalable and cost-efficient architecture, while also ensuring a seamless migration of data pipelines.
Migrate existing system from on-premise to more scalable and cost-efficient cloud architecture that will increase flexibility and reduce costs
Ensure a smooth migration of data pipelines to the cloud architecture maintaining existing business logic and functionality
Improve the clinical data validation process for better accuracy, integrity, and compliance
The NIX team migrated the existing solutions from an on-premise Hadoop ecosystem to an Azure and Databricks technology stack. We also designed multi-tenancy architecture that is easy to scale, can resist peak loads, and ensures Infrastructure as Code (IaC) availability, while taking into account potential technical and business risks.
The NIX team opted to switch from the SAS programming language to Python, as Python is not only easier to maintain on Azure but also provides better cost-efficiency. The adoption of a single language for data engineering also proves to be more efficient. We integrated Octopus Deploy with Azure DevOps to provide a fully-automated build and deployment pipeline, improving resource utilization and ultimately leading to cost savings.
We orchestrated the migration of the client’s pipelines, shifting them from on-premises servers to the Azure platform and ensuring a smooth data exchange between databases and storages. At present, our efforts are focused on the transformation of PySpark scripts into Azure Databricks, alongside the development of pipelines within Azure Data Factory to execute these scripts effectively.
For orchestrating ETL/ELT pipelines and data enrichment processing, we leveraged Azure Data Factory and Databricks. Databricks Delta Lake was used as a main data warehouse and contains all the historical, procedural, clinical quality enrichment data. Azure Databricks serves as core for data processing and migration of existing Pyspark jobs.
On the Azure side, we also implemented table comparison service for comparing input/output data in Azure and on-premise by certain filter criteria to ensure uniformity.
Leveraging Apache Spark, we established and refined the processing and validation of hospital data, including patient personal information such as diagnoses, age, gender, payments, procedures, and prescription treatments.
Our team of data engineers devised validation rules to rectify discrepancies and implemented sophisticated data quality monitoring capabilities for clinics. This prevents the system from processing data files containing significant disparities, thereby ensuring superior accuracy, data integrity, and regulatory compliance.
Through the adoption of a cloud-centric infrastructure and the enhancement of data pipelines, NIX enabled the client to offer healthcare and insurance providers cost-effective, secure, and data-driven solutions, resulting in improved patient outcomes and reduced operational expenses.
The solutions leverage raw clinical and supply data to deliver valuable insights through advanced data visualization capabilities, all the while upholding robust data processing, strong security, and data integrity.
6 Data Engineers
Python, Azure, Azure DevOps, Django, Pandas, PySpark, Spark, Hive, Azure Data Factory, Azure SQL Database, Azure Databricks
Web platform for building curricula with pre-built 3D lessons and slides from anatomy educators across the globe.
Web and mobile HIPAA-compliant app for improving patient retention and measuring patient health remotely.
Interactive NLP chatbot empowered with conversational AI for web, mobile, and desktop that accelerates internal operations.
NIX team designed a robust Power BI solution that plays a pivotal role in empowering our client to offer unparalleled benchmarking opportunities.
AR-based mobile application for managing diabetes that empowers diabetic patients with healthy food recommendations with 3D food models in an interactive way.
NIX developed a backend service ensuring smooth and seamless communication between components of the clinical trial system.
Blockchain-powered SaaS solution designed to help medical companies work with patient data in a secure way.
AWS data analytics platform for an educational 3D platform that provides actionable insights on marketing and product activities.
How NIX helped leverage data science and artificial intelligence for digital transformation of Assisted Reproduction field.
See more success stories
Our representative gets in touch with you within 24 hours.
We delve into your business needs and our expert team drafts the optimal solution for your project.
You receive a proposal with estimated effort, project timeline and recommended team structure.
Find out more about top mobile development technologies, their pros and cons, and which ones will help you meet your business goals.
Migration to the cloud is one of the most popular areas for digital business development today. However, the chosen approach doesn’t always meet the expectations of business owners, primarily because of its obsolescence. So let’s find out the 15 hottest cloud trends that will help boost your business processes in 2022.
By investing in MVP software development, you can assess the validity of a business idea behind a software product and pinpoint its strengths and weaknesses.
Understanding the types of data is crucial to mastering data analytics techniques. Explore structured vs unstructured data and learn their benefits and applications.
This article describes how your business can reduce operational and IT costs with help of tech solutions during a global crisis while maintaining business growth.
Report generation is a highly skilled activity that requires a robust solution. Learn about ServiceNow reporting and its capabilities and best practices.
Digital marketing and machine learning: advanced technologies as the key to success for your business.
Not all business owners believe that digital marketing can help them improve ROI and target the right audience. Learn more about the reasons to invest in digital marketing campaigns from this post.
Knowing exactly what data tasks you may tackle with business intelligence and data analytics without confusing the two may be your business game-changer.
See more insights
Schedule Meeting
