Data is everywhere, and only through proper analysis can relevant insights be obtained. Taking data simply at face value and not delving deeper can lead to inaccurate conclusions and missed opportunities.A key part of both my career and education in science has been the collation, analysis and understanding of data from a wide range of sources. From understanding the properties of novel chemicals to the optimisation of device performance for flexible electronic devices, data has always been produced as part of the process. However, data on its own is not beneficial, requiring the appropriate analysis to extract usable insights that can feed back into further developments and customer expectations. Examples from my career include:• Analysis of complex device performance datasets to aid in development of organic semiconductor formulations which were later sold to a third party bringing £1.5 million into the business.• Analysis of image data to bring novel insights into areas from cell microscopy to aerial surveying.• Analysis of flexible electronics samples to identify routes towards bringing customers’ novel concepts towards prototyping.Sometimes this analysis can be straightforward, however many times it is not, and for me the real challenge and interest can be to explore how data needs to be manipulated, interrogated, and visualised to gain the most informative insights for stakeholders.Inquisitiveness and curiosity led me to investigate how to escape the limitations of what Excel alone could do, initially using visual basic code to streamline data collation and analysis and then making use of Python to expand my data collection, manipulation and visualisation capabilities when the solutions I had to hand proved insufficient. I enjoy the challenge of exploring technologies that are new to me, needing to quickly learn MATLAB® for a role was an interesting learning opportunity rather than a potential roadblock.This interest in learning and my desire to find better approaches to handling data has led me to the field of Data Analytics and through the LSE Data Analytics Career Accelerator I am taking my skillset to the next level to be able to move my career in this direction. Not just building on my existing Excel and Python knowledge, but expanding further into using Tableau, SQL and R in the field of Data Analytics.I’m looking forward to the next challenging opportunity in my career to bring my new skills in data analytics along with my previous experience as a research scientist to help solve new and interesting data challenges.