A new prescription for big data headaches in pharma-tech

Every industry runs on data. From oil rigs to bakeries and from finance to dressmaking, every business now has a responsibility to re-define itself as a data-centric software business. The pharmaceutical industry is no different. A new reliance upon big data analytics functions and an increasing amount of AI-driven insight are creating a new type of pharmacological operational dynamic.

healthcare data breach / medical patient privacy security violation
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Whether we call it pharma-tech, life sciences or perhaps even health-tech, a new data-driven health industry is emerging.

Big data analytics has already proved an effective means of fuelling development in drug research, so in this respect, its impact is being felt at the procedural end of the industry. But data analytics also helps at the human level. Providing insight into patient care needs for care-workers and helping them to make sense of the noise around them in busy working environments, it can provide schedule-based reminders to inform when medication needs to be distributed. It can also provide automated alerts that track warning signs to signify when patients may be becoming increasingly unwell.

Noisy data everywhere

That element of ‘noise’ pervades throughout healthcare into what we could call data noise. Even the most modern healthcare practices operate with operational silos and fragmented facilities management and billing systems. Add that complexity to the fragmentation that occurs between different medical service lines… and its clear to see how complex data can spiral upwards and start to represent a health risk in and of itself.

The answer that some firms in this space are adopting has a front end and back end element. At the front end, data visualisation technologies are helping to coalesce complex data sources and provide dashboard illustrations that express the live state of operations in any given facility.

But at the back end, pharma-tech data warehouse systems also need a booster shot. For databases, that advantage can come from Graphical Processing Unit (GPU) accelerated power that has the power to handle gigabytes, terabytes and even petabytes.

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