Data-driven insights have always been a critical piece in operations of care delivery organizations. Data is also at the core of disruption in the healthcare industry. This could range from complicated machine learning based clinical decision-making platforms or behavioral analytics to understand and enhance patient experience. Data engineering is a critical focus area for any digital health platform team.
DIGITAL HEALTH PLATFORM ENGINEERING CASE STUDIES
Healthcare Data Engineering Challenges
From high velocity IoT data to huge datasets of genomics and radiology, healthcare presents a true big data challenge to healthcare platform teams. Processing healthcare data is not just about high-performance data processing platforms—managing complex evidence-based clinical guidelines and administrative / compliance rules makes it even more challenging. Similarly, apart from the usual data visualization complexities, such solutions also have to cater to regulatory submission standards. In addition, there are data security issues. Thus, healthcare data engineering teams have a challenge unparalleled in other industries.
Our Healthcare Systems Engineering Expertise
Cybage has immense experience in implementing data engineering platforms—not just in healthcare but across industry verticals. Cybage takes a holistic view of data engineering requirements, which is why our multifaceted approach includes traditional data warehouses and modern data lakes, cutting-edge DevOps, ETL lifecycle management, 24x7 support model, and so on.