Utilizing MapReduce to address Big Data Needs in Pharmaceutical Segment

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We are all aware that with each passing year, organizations of all sizes are generating massive amounts of data that when analyzed properly, can deliver a true competitive advantage in today’s fast-paced environment.

Pharmaceutical and life sciences organizations are challenged with how to innovate for differentiation, reduce costs and shorten drug development cycles. Given the amount of data generated by pharmaceutical companies, the information hidden in their stores of data holds the keys to faster development, increased efficiencies in addition to improved and faster ROI. Pharmaceutical companies are becoming more sensitive to this and are increasingly looking at Big Data in order to metamorphose the data deluge challenge into an opportunity with a potential for a competitive advantage.

In order to drive actionable insights from ever growing data, there needs to be a unified technology platform to make managing, storing, processing and analyzing Big Data faster and more efficient. Latest IT trends such as the evolution of Graphical Processing Units (GPU) deployed on Cloud Infrastructure provides enormous compute facilities, which when leveraged with well-defined distributed processing layer, is capable of handling data and bringing out intelligence hidden within.

In the first eBook, Utilizing MapReduce to Address Big Data Enterprise Needs, we have introduced the High Performance (GPU) & Cloud Computing Enterprise Solution that utilizes the MapReduce Paradigm, designed to solve relevant workflows and provide new insights into the increasing data available during different process stages. In this eBook you can also learn about the use cases of histology (microscopy) data which underline the need for enterprise software platform to upload, store, visualize and analyze medical data in a high performance environment.

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