The high volume of data from Electronic Health Records (EHRs), Medical Imaging, Genomic Sequencing, Payor Records, Pharmaceutical Research, Wearables and Medical Devices, makes Healthcare data a challenge to process and convert into useful, actionable information.
Tech Vedika was approached by a leading multinational Healthcare Company to help their Global Customer Support team to analyze telemetric run data of Next Generation Sequencers. The process involves a complex analysis of the logged instrument data. Each analysis run could generate 100s of GBs of data.
Tech Vedika’s Data Analytics Lab built a novel system on top of scalable computing and storage Hadoop framework. The system ingests large data sets from Transcript Expression Analysis along with the metadata and builds a data model for efficient analysis.
Following are the few salient features:
- Expose Web Services/Queues to integrate with other downstream systems
- SQL engine on top of a distributed system for ad hoc analysis
- Auto management of complex workflows
Our solution ingests 100s of sequencing runs and processes 100s of GBs of data daily to enable global support team to investigate failed runs in a timely manner. Our data model crunches large data sets to bring actionable information using machine learning. The visualization dashboards enable easy navigation through actionable information to understand the root causes of the failures.