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Technical Talk on Big Data at Amrita Vishwa Vidyapeetham, Mysuru Campus

October 16, 2017 - 10:04
Technical Talk on Big Data at Amrita Vishwa Vidyapeetham, Mysuru Campus

A technical talk for the final year MCA students of Amrita Vishwa Vidyapeetham, Mysuru campus, on Big Data and its scope in industry was held at the campus on October 13, 2017. The resource person was Manohar L., Senior Technical Expert, HPE Micro Focus and team. The students were exposed to various trends in Big Data and they were given an idea on the technologies that can make them experts in data processing and analytics.

The major topics focused on were Big Data industry perspective, applications of Big Data and analytics used in industry and the relevance of Big Data. He also gave real-time examples of Big Data implementation in areas like social media websites, sensor-based applications, Big Data applications in healthcare, manufacturing, media & entertainment, IoT and in various data repositories needed for Government.

One of the major applications that was discussed in the session was healthcare, as the data generated there is enormous. Traditionally, the healthcare industry did not operate on Big Data due to limited ability to standardize and consolidate data. Recent surveys conducted reveal that Big Data analytics have improved healthcare by providing personalized medicine and prescriptive analytics. Researchers are mining the data to examine the methods of treatments that are effective for particular health conditions, identify patterns related to effects of drug intake and gain other important information that can advise the patients and help ineffective cost reduction.

Mr. Manohar L. stressed that with the added adoption of mHealth, eHealth and wearable technologies the volume of data is increasing at an exponential rate and it also includes electronic health record data, imaging data, patient-generated data, sensor data, and other forms of data.

He mentioned that by mapping healthcare data with geographical data sets, it is possible to predict diseases that might escalate in specific areas. Based on predictions, it is easier to strategize diagnostics and plan for stocking serums and vaccines. The talk was informative and effective for the students and was supported by real-time demonstration.

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