Making sense of the data we collect
Sourced through Scoop.it from: www.techradar.com
Human applications: Big data can be used to help solve real-world problems, like cancer research in healthcare. Intel’s goal is to be able to map the human genome in one day to deliver precision healthcare that’s personalized towards the patient by 2020.
Why is precision healthcare important? The primary reason is that treatment can be performed outside of the hospital. Intel says that the US spends $10 billion a year to fight infections contracted while patients are in the hospital. With IoT devices and remote medicine, patients can seek in-home care and therapy, rather than risk infection in hospitals, in many instances. – In an Oregon trial, Intel provided 450 people with a connected blood pressure cuff and the Basis Peak smartwatch. These devices provided 300 million data points per night, which is more data than what can be collected in a doctor’s office visit. – In helping to analyze and share this data in a safe and secure way, Intel announced its new Collaborative Cancer Cloud. Intel says that even when we have abundant collected data, the information is trapped because researchers are worried about the security implications of sharing. The benefit of sharing is that it can help speed up research, provide more rapid diagnosis and treatment and help researchers develop cures at a faster rate. To help researchers, the Collaborative Cancer Cloud will create a secure virtual machine for data to be shared. Once the information is shared, data is then wiped, said Diane Bryant, Intel Vice President and General Manager of Intel Data Center Group.
Making sense of the data: Commercial IoT requires a platform that helps users make sense of the collected data with a scalable and flexible platform with tools, resources and technical support.
Bryant claims that data is “the currency of the digital world,” but that it takes more than just data. Once data is collected, how do you make sense of the data? Understanding the data is changing the conversation from data to algorithms, and this shift resulted in Harvard Business Review naming data scientist the top job of the 21st century.