Data lakes — aka graph databases — can store vast quantities of raw structured and unstructured data in its native formats in a centralized repository, allowing researchers to combine disparate data sources in unique ways. That makes them particularly well suited to healthcare, given the wildly variable nature of data generated by the likes of EHRs, insurance claims, medical devices and wearables.
For example, Partners HealthCare in Boston has launched an ambitious project using data lake technology to support research into precision medicine and the IoT. The goal is to build an infrastructure platform, called the Integrated Data Environment for Analytics (IDEA), which numerous different researchers can securely share for their Big Data analytics projects — thus eliminating the need for each group to start from scratch.
Other advantages of using data-as-a-service platforms such as IDEA include:
- Virtually unlimited storage capacity
- Flexibility for cloud-native applications
- A modular approach that supports scalability
- A streamlined process for generating actionable insights
Learn more about how data lakes and data-as-a-service platforms can help researchers and clinicians translate Big Data into new care guidelines, clinical decision support and precision medicine.