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Pharma

Radiology Data Lake

Life Sciences
case study

Business Impacts

Accelerated R&D operational processes

Migrated and stored 9+ petabytes of data

Customer Key Facts

  • Location : Europe
  • Industry : Pharmaceuticals & Life Sciences

Problem Context

The collection and storage of radiology data is often a laborious and manual task for organizations with several data sources and a lack of infrastructure. Such a process is time-consuming and may fail to uncover insights that have useful business implications. Additionally, organizations that do not have proper data analytics systems in place experience difficulty in harmonizing multi-source data and running a unified set of analytics across the data sets.

Challenges

 

  • Large datasets
  • Compatibility of ETL tools with customs scripts
  • Authentication challenges for pulling and pushing data into data lake
  • Maintaining Data integrity

Technologies Used

Cloud Dataflow

Cloud Dataflow

Google's BigQuery

Google's BigQuery

Cloud Dataproc

Cloud Dataproc

Cloud ML

Cloud ML

Cloud Pub/Sub

Cloud Pub/Sub

Cloud Datastore

Cloud Datastore

Cloud Storage

Cloud Storage

Cloud Functions

Cloud Functions

Tableau

Tableau

Google Data Studio

Google Data Studio

Digital Transformation of Radiology Data Ecosystem

The customer, one of the largest multinational pharmaceutical and life sciences companies wanted to build a long-term system for storing, curating, and sharing medical images and patient healthcare information curated from multiple sources and leverage this data lake to work on cutting-edge machine learning and analytics solutions in the healthcare domain.

Solution

Leveraging Google’s HIPAA compliant products, like Healthcare API, Cloud Dataflow, and BigQuery, Quantiphi built robust radiology data lake with a customized and integrated DICOM viewer and annotation tool for day-to-day access and analysis. This brought everyday radiology workflows onto a scalable and flexible platform driving collaboration, growth, and innovation; thus, helping the organization to unlock vital insights from radiology data.

Results

  • Improved data quality
  • Democratized data for faster, better decision-making
  • Flexible user management

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