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The Student Insider

Why a post-COVID recovery will be data driven


Written by
Lauren Katalinich

In many ways, the months of the coronavirus pandemic have been a period of unique cooperation and unity. We have seen governments take charge to protect citizens, citizens take responsibility for protecting one another, and companies do their bit to give back. But one pivotal actor driving change behind the scenes of this story has been that of intelligent technology - and the data science that underpins it.

Using mobile technology for data science

This was the first global crisis that relied on tech to get us through it. After all, as the world locked down, our lives went almost entirely online. There to greet us were the many streamlined services that had been designed specifically to enable us to remain safely on our sofas. Amazon, with its heavily automated supply chain ensured speedy home delivery of everything from protective masks to painting sets. Artificial intelligence powered the logistics systems of Deliveroo, while streaming services like Netflix and Spotify kept us entertained with algorithms to tailor offerings to our personal tastes.

Dr Jamie Ward, a lecturer in machine learning at the University of London’s MSc Data Science, explains how it was the boom in big data that enabled this world of remote working, online shopping and home delivery.

Without the algorithms behind them, the logistics of these services would be impossible, he says. Fifteen years ago, ten years ago, we would have been living in a much less comfortable locked down world. The tools of machine learning allowed for business continuity.

But data science is not just a tool for convenience in the marketplace. When acting in times of crisis, we must always consider our options and make a swift decision using the information we have at hand. That is not always easy, particularly when that information comes in the form of large and cumbersome data sets. But this is exactly what data science excels in. Throughout the pandemic, governments and health organisations have relied heavily on its systems to make informed decisions.

Data science was the architect behind many of the COVID-19 public health mandates, for example. Orders to stay at home, wear masks, and adhere to social distancing were the result of analysing an enormous set of data of the disease’s behaviour worldwide. Had there been larger and more accurate data sets from initially infected countries, many argue, we could have created better models using data science to predict and curtail its spread.

A data-smart future

We have many lessons to draw from the events of COVID-19 but perhaps one of the most critical is the importance of being able to use data to prepare for potential scenarios and inform our decision making. There is a real and urgent need for those with the skills to crunch data quickly, and to implement the data strategy needed for this analysis and processing.

As the world prepares for ‘the new normal’ post-pandemic, and all the economic, social, and political question marks that loom above it, many are looking to the tools of data science to continue to help us inform our trajectory. Advanced data science, and the technology it powers, is rapidly becoming an essential component of nearly every industry in both the public and private sectors.

A huge area for further work in data science post-COVID will of course be in healthcare with the introduction of contact tracing apps, remote consultations, and remote monitoring devices. Development of medical solutions and understanding the patterns of a pandemic involve large, complex data sets which are perfect for the tools of data science.

On a public level, local and regional governments under new economic strain are looking to make a rapid transition to smart city infrastructure with intelligent solutions for traffic control, crime prediction, and data sensors that could lead to more effective policing and administrative efficiencies.

In the private sector, businesses are likely to beef up their data strategy in order to build simulations and forecasts that will allow them to better prepare for disruptive events in the future. With these potential risks clearer, businesses can create plans for business continuity. For example, many companies suffered from a breakdown in their usual supply chains during the pandemic. As a result, they are reassessing their structures and will likely turn to cutting-edge automation for answers, including 3D printing technology, robotics and automated factories that will help bring production closer to consumption.

However, a key concern with developing and rapidly deploying these new models are the vulnerabilities that come with them and risks to security and privacy as a result. Ensuring that these systems are ethical and transparent will be more important than ever.

We will need data scientists to ensure these technologies are fit for purpose and responsibly designed and deployed. The University of London’s MSc Data Science programme is helping to address the shortage of these critical skills in the marketplace and in the public sector. It gives students an understanding of the fundamentals of data science to solve real world problems while allowing them to specialise in particular areas such as Artificial Intelligence and Machine Learning.

If you want the skills to help build a resilient future of responsible technology, consider the University of London’s Data Science programme. The course, which is delivered online by design, can be studied from anywhere in the world and at a pace convenient for you.