Big Data in Pharmaceuticals Industry

This thesis examines the pharmaceutical industry and the changes that have occurred, in particular, over the past 10 years as a result of the general economic downturn, rising health costs and costs associated with the development and sale of pharmaceuticals and the era of Big Data. The increase of the availability and growth rates of information available to the a pharmaceutical company, also known as Big Data makes it possible to create not only personalized medicine programs that will significantly improve patient care, but also enable the use of big data technologies to obtain insights from data that, at first glance, do not correlate with each other. This work contains an algorithm for calculating the endless stock of goods for each pharmacy of the pharmacy chain for a certain product, based on data that any pharmaceutical company can have. This method shows that the available data can be important and valuable for the business, and their analysis can help sales representatives make data-based decisions while negotiate with a client, which will give the maximum benefit without spending the entire budget. First of all, this work may be interesting to pharmaceutical companies, as well as other retail companies that have a similar data structure.