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Ten Major Challenges of Big Data Analytics in the Healthcare Industry of Today

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The hype surrounding big data analytics in healthcare can be termed as “challenging, but inescapable” with the providers like Datafloq feeling the highest pinch of it. The need to reliably store the data today, safely and securely, and be sure that it will be efficiently accessible particularly useful in healthcare when needed adds to the excitement. Big data is long, complicated and bulky, often requiring taking a closer look at more vital aspects of it to ensure that it becomes meaningful.

Forget about the enormous enthusiasm regarding how “big data” will address continuous cost and quality deficiencies in the system, interpreting and successfully integrating them isn’t a mere walk. Clinical and IT departments with narrow focuses that solve a single problem at a time are the ones who feel the pressure even more. And those who have barely understood how to convert them into Electronic Health Records (HER) are now required to highlight actionable insights out of the data.

Clearly, the pathways to meaningful healthcare analytics are thorny ones even though some of the perks are healthier patients, lower healthcare costs, and higher consumer satisfaction. The facility will first have to collect, store, analyse, process and present the data to its stakeholders …

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