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The coronavirus pandemic has created many shifts and changes in society and business, particularly in the technology industry, which has seen even higher levels of engagement during the health scare. People have turned to technology to feel connected with their friends and family, as well as to conduct business. This is an observation that has been noted by industry professionals including Thibaut de Roux, who is involved in a start-up that focuses on big data, AI, tech and digital.

Big data is one of the most precious and valuable assets of our age. However, for it to be truly valuable, it must be processed. The sheer volume of data available means that it is essential to use technology and data science to arrange and organise it into useful information and understandable insights. Machine learning is one of the technologies that has been applied to big data, particularly in the fintech industry, where it gathers and organises big data into digestible information – and it has also been mentioned as a potential panacea to the global Covid-19 pandemic.

With regard to the coronavirus, big data can be used to allow meaningful modelling and analysis. However, the tools that we currently have at our disposal are both slow and costly. Data science, scientific computing and machine learning would all be required for modelling and analysis by ETL – extract transform load – and therefore, a solution is more likely to come from high-performance computing (HPC) or supercomputing.

Covid-19 has drawn a great deal of attention to the role that big data and technology could play in understanding the virus, its impact, and any possible solutions to this problem. Currently, there are a number of simulations and models being run that hope to understand how the virus is spread and transmitted, including complicated real time and non-real time simulations.

The problem posed by the Covid-19 pandemic, in terms of big data, is that it requires big compute capabilities as well as big data capabilities. Therefore, cloud technology is being used to scale dynamically as the situation evolves. The development and advancement of these technologies is paramount during the Covid-19 crisis, so that we are able to develop reliable and accurate models from vast, global data sets.