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San Francisco-headquartered data and AI company Databricks today expanded its product portfolio with another vertical-specific platform – Lakehouse for Healthcare and Life Sciences.

The offering, as the company explained, brings a set of tailored data and AI solutions aimed at solving the most common challenges enterprises face while innovating in the healthcare industry. It follows the launch of Databricks’ lakehouse for retail and financial services sectors.

“As organizations fully transition to electronic medical records, new data types like genomics evolve, and IoT and wearables take off, the industry is awash in massive amounts of data. But…teams don’t have the tools to properly use it,” Michael Hartman, senior vice president of regulated industries at Databricks, said. “With Lakehouse for Healthcare and Life Sciences, we can drive transformation across the entire healthcare ecosystem and help empower our customers to solve specific industry challenges and drive better outcomes for the future of healthcare.”

How would Lakehouse for healthcare help?

Currently, enterprises in the healthcare sector largely rely on legacy data architectures that keep information from different systems and functions in fragmented silos. This makes advanced analytics difficult, restricting the pace of innovation across areas such as patient care and drug discovery.

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The vertical-specific lakehouse, on the other hand, eliminates this challenge by providing health institutions with a single cloud-backed platform for data management, analytics and advanced AI. It enables organizations to leverage data easily and accelerate the development of more advanced, data-driven solutions such as those aimed at disease risk prediction, medical image classification, biomarker discovery and drug development. Cross-functional teams – from physician-scientists to computational biologists – can also use data from this product to build a holistic view of the patient and make real-time decisions.

To make these applications simpler, Lakehouse for Healthcare comes with a bunch of solution accelerators and open-source libraries (such as GLOW for genomics) backed by a certified ecosystem of partners. When combined together, these elements help data users jumpstart their analytics projects and save weeks to months of development time.

The partner ecosystem, Databricks explained, includes companies like Deloitte, Lovelytics, John Snow Labs and ZS Associates. John Snow Labs will help enterprises analyze unstructured medical text using NLP for use cases such as oncology research, drug safety monitoring and anonymizing personal health information. Meanwhile, Lovelytics and ZS Associates help with automating the ingestion of streaming Fast Healthcare Interoperability Resource bundles and improving biomarker discovery for precision medicine. 

Customer base

Databricks is making the new lakehouse offering generally available starting today. However, some enterprises have already had a chance to use it early, including GE Healthcare, Regeneron, ThermoFisher and Walgreens.

“The Databricks Lakehouse for Healthcare and Life Sciences is helping GE Healthcare with a modern, open and collaborative platform to build patient views across care pathways. By unifying our data in a single platform with a full suite of analytics and ML capabilities, we’ve diminished costly legacy data silos and equipped our teams with timely and accurate insights.” Joji George, CTO of LCS Digital at GE Healthcare, said.

The move further expands Databricks’ lakehouse ecosystem, which competes directly with Snowflake’s data cloud. Other players in the same space are Dremio, Google BigQuery, and Amazon Redshift.

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