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1. BUSINESS INTELLIGENCE APPLICATIONS FOR DATA ANALYSIS SOFTWARE
2. BUSINESS INTELLIGENCE APPLICATIONS FOR DATA ANALYSIS TRIAL

“…applying big-data strategies to better inform decision making could generate up to $100 billion in value annually across the US health-care system, by optimizing innovation, improving the efficiency of research and clinical trials, and building new tools for physicians, consumers, insurers, and regulators to meet the promise of more individualized approaches.”

BUSINESS INTELLIGENCE APPLICATIONS FOR DATA ANALYSIS SOFTWARE

McKinsey defines it as “ datasets whose size is beyond the ability of typical database software tools to capture, store, manage, and analyze”.Īccording to the McKinsey Global Institute: The extracted information is then visualized in an interactive way through charts, diagrams, and graphics.īig Data refers to a large number of both structured and unstructured data. The answer is Business Intelligence.īusiness Intelligence (BI) software is a new cutting-edge pharma big data solution that provides a real-time data analysis based on numerous internal and external sources.

Outpacing Rivalsīefore releasing a new drug product or pharmaceutical research, companies need to be aware of the market situation in their sphere / However, the challenging part lies in the fact that the pharmaceutical companies constantly release new products and perform new trials, which are difficult to keep track.

BUSINESS INTELLIGENCE APPLICATIONS FOR DATA ANALYSIS TRIAL

However, to comb through in order to find v aluable insight into patients’ reactions to a particular drug, adverse effects they might experience or the number of patients enrolled in the trial – is a very challenging and difficult process, especially when performed manually. Results of past clinical trials and tests are very important for ongoing and future ones.

However, to gain these insights, pharmaceutical companies need to process and analyze huge amounts of constantly growing data in real-time. The influx of data generated by consumer-based health devices, namely wearable gadgets allows drug companies to directly collaborate with customers, receiving from them important data related to reactions to particular drug elements or general health conditions. The major of them are related to constantly produced data.

Utilization of advanced tools, such as BI services, Artificial Intelligence or Augmented Analytics in pharma is the key to success in this business which is basically based on the data generation.īusiness Intelligence solutions and Pharma Analytics systems are actively applied by pharma companies to better harness valuable data, identifying the most suitable candidates for potential drugs.Īccording to the Worldwide Health Industry 2020 Predictions report, IDC professionals claim that the next decade will be defined by healthcare data and the technologies needed to harness them.Īccenture and IDC Health Insights conducted a survey across 126 pharmaceutical and biotechnology leading companies from the United States and the United Kingdom and found out that most surveyed enterprises have a strong consensus about the importance of data.ĭeveloping a pharmaceutical product requires a lot of effort, which self-evidently entails many challenges. We live in the post-data era – the time, when huge amounts of data have been already produced and the current task is to process them for a more accurate perception of the pharmaceutical market, as well as companies’ internal processes and ongoing clinical trials. The pharmaceutical industry and life science are more and more focusing on state-of-the-art technologies based on advanced pharma data analysis.