Intel’s Health Care Expert on Analytics’ Role in Personalized Medicine

by   |   December 11, 2013 6:04 am   |   1 Comments

Ketan Paranjape of Intel

Ketan Paranjape of Intel

Intel, long known for its computer chips, has been making steady investments in big data analytics. In February, Intel had a kind of big data coming out party when it made its own version of Hadoop available to the open source community.

On this episode of the Data Informed podcast, Ketan Paranjape, the global director of health and life sciences at Intel, talks about his efforts to build on those investments as he discusses the current state and future directions in health care analytics. The goal of this work, Paranjape says, is to collect and analyze data that can do everything from assess public health trends in a region of millions of people to pinpoint treatment options for one cancer patient.

Paranjape works with research and development teams in software and hardware, with health care researchers and numerous external partners to build out data management infrastructures. His team works on advanced projects with a range of players in health care around the world, from insurance companies to medical researchers to drug makers, hospitals and biotech firms.

One project involves working with regional health officials in Jinzhou, China, using Hadoop as part of a system to store, manage and analyze records for more than 3 million residents. At another, IT staff members at the Charité Universitätsmedizin Berlin Hospital are using Intel processors and SAP’s HANA in-memory processing system to perform ad hoc reporting on records covering about 700,000 patients.

In the podcast interview, Paranjape discusses the challenges that these and other projects represent for IT and analytics professionals working to manage issues like the quality of patient data and cultural resistance to changes brought about by implementing data-driven processes.



Michael Goldberg is the editor of Data Informed. Email him at Michael.Goldberg@wispubs.com.

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Intel Jumps into Big Data Pool with Hadoop Distribution









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One Comment

  1. RodrigoS.
    Posted December 26, 2013 at 11:36 am | Permalink

    great article !

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