Biotech is one of the impactful industries, its innovations helps provide treatments to cure diseases and bring new products which can help build sustainable communities. Data forms the web between biotechnology ecosystems. Data helps to integrate companies, stakeholders, people, information, and processes in bio tech volume & variety of information in bio-tech industry grows, we could use analytics to refine it in the advantageous way to make decisions. As a part of our project, we propose an analytic methodology that proposes an alternative way to look at data that could diminish R&D expenses of the biotech business by half, additionally assisting with assembling to decrease the number of the failed batches. As biotech organizations are continually under the monitorization of the FDA it’s very critical to keep up the standards provided, Investing in big data analytics tools like Pi, Statistica and visualization tools like Tableau, Spotfire and SIMCA that provides biotech firms a constant monitoring platform of data generated from Day 1 of cell culture to end of the batch and control charts generated from the data provide a means to identify any batch failures/ unusual performance of the batch leading to corrections/ batch termination in manufacturing plants preventing loss. The right use of Data Analytics could help generate business esteem & drive innovation.