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Enabling IT Transformation of traditional BI to Big data analytics in Healthcare industry

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by Dinu Davis
23 April 2015

The amount of data generated in the Healthcare industry from different sources like Pharma R&D, physicians, retailers and patients has been increasing exponentially. The current Business Intelligence (BI) tools handle data sources as isolated entities. Advent of big data technologies into analytics bring together these independent entities to provide meaningful insights at a portfolio level to help in strategic decision making. This article discusses the relevant IT Transformation required to enhance the existing BI practices to the new age Big Data analytics. The key focus will include shift in IT tools and the sourcing approach to enable this transformation. Business intelligence (BI) tools are used for reactive analytics like descriptive analytics and diagnostic analytics. Reactive analytics are used to understand and analyze the reason for the past events like spread of a disease in certain geography in winter season. However, proactive analytics which includes prescriptive and predictive analytics is addressing future problems and provides action points. Proactive analytics can predict the demand for vaccines accurately for next year to fight a particular disease considering different factors like variation in climate, vaccine production rate, life style of the population etc. Business intelligence tools lack the capability to handle the exponential growth of data in healthcare industry, majorly comprises of videos, text and voice, which is quite unstructured. However, big data is able to adapt to the current data volume requirements and integrates multiple data sources enhancing data processing. Suppliers cater to big data analytics technology belongs to 4 phases of big data deployment namely acquisition, organization, analysis and action which specific skill-set apt at each activity. There are pure big data vendors who provide analytics solutions like Palantir and Splunk, while software giants like IBM, Microsoft, Oracle etc. also include big data solutions in their product portfolio and provide as an end to end solution. Though big data investments are strategic in nature, break-even is expected at 12-18 months after implementation through direct cost savings.

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