How Organizations Use Big Data Analytics and AI to Manage Pandemics

The danger of worldwide pandemics became all too real recently with the spread of the novel coronavirus (COVID-19). While the strategy for identifying and containing disease outbreaks on a global level is a complex issue, there is one thing that is becoming clear: fast analysis of available data can and is aiding the battle. 

Big data analytics are helping to bring new hope to stopping the spread of pandemics, among many other public benefits. Today, over 97 percent of organizations are investing in big data and artificial intelligence, and according to a recent McKinsey study, 30 percent of respondents are using big data to improve the research and development function across multiple industries, including in epidemiology. 

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Decentralizing Data Analysis

When it comes to tracking the spread of diseases, the biggest challenge for authorities in the past has always been the speed with which they can gather and analyze breaking information on outbreaks as they grow. The analysis was traditionally too centralized, and far too slow. For example, in the United States, healthcare providers participate in the “Influenza-like Illness Surveillance Program” to monitor the spread of the flu, according to a recent report from Nature. This involves filing weekly reports of likely cases and samples from patients for testing. Results are evaluated centrally in testing centers, but it can sometimes take weeks to identify and respond to an outbreak. 

Big data analytics can help de-centralize the process and provide a much faster means to analyze widespread datasets. Even the IoT (Internet of Things) is connected, as individuals are increasingly using mobile phones to provide real-time health information (such as flu symptoms) that can be quickly accumulated and analyzed to track disease spread. The faster this information can be gathered, evaluated, and acted upon, the safer the population will ultimately be.

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Analyzing Genetic Data and Online Behavior

Another way that big data analytics can help stem the spread of pandemics is in analyzing vast amounts of data derived from modern methods of genome sequencing. Scientists can observe in real-time how a virus mutates during an outbreak, then share and track that information with others. Big data is also empowering a new generation of high-resolution computer-generated simulations, interpreting large disease-related datasets that show how an outbreak could be spreading. Faster analysis of all of these types of data means greater ability to collaborate and a more rapid response to an outbreak. 

Big data can even help fight pandemics by monitoring internet or social media activity in the early stages of a potential outbreak, according to a report in National Geographic. Big data analytics can spot behavioral patterns online, such as a rise in online searches for a particular disease or its symptoms, or mentions on social media of an illness that can help track the spread in a geographic area. There is a wealth of information and insights produced by millions of individuals online, and big data analysis can help spot it quickly to help authorities respond. 

Learn What’s Driving Big Data Frameworks

Today’s big data frameworks revolve around the Hadoop ecosystem, and Big Data Architects are the key players that can connect the dots between robust technology and business solutions. Technologists who undergo this comprehensive Hadoop training can design Hadoop big data frameworks and manage large-scale deployments. Hadoop relies on a number of key supporting technologies such as the Apache Spark open-source framework and Scala programming language, MongoDB development and administration for NoSQL databases and data modeling, and Apache Kafka for open-source messaging in the big data framework. 

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Contributions by AI and Machine learning

As with many other industries, AI and machine learning are bringing a new generation of tools to the big data analytics market. In fact, 59 percent of executives say big data at their company would be improved through the use of AI, according to PwC. AI is the ideal engine for spotting trends as a virus spreads during a pandemic, for example, and it can keep up with changes in real-time to provide the most accurate current information for healthcare workers and authorities to stay ahead of an outbreak. 

It should come as no surprise, then, that demand for workers with AI talent has more than doubled over the past three years. For data-driven organizations, aptly trained AI engineers utilize the latest algorithms and tools and applying them to solve real-world problems, such as managing data in the fight against epidemics.

Tracking and responding to global pandemics is certainly a complex, broad-based challenge. Fortunately, scientists and health care professionals can rely on big data analytics tools to more quickly track and analyze the spread of infectious diseases. Perhaps nowhere will big data’s impact be felt more strongly than in cases like this to keep human populations safer. 

Join the Fight 

Without a doubt, big data analytics and AI will ultimately touch every part of our lives. This means that there is a need for people who know how to work with it. Simplilearn offers comprehensive training to give you all the skills you need to make a successful career. Our Integrated Program in Big Data and Data Science—among many others we offer—could get you well on your way to becoming part of the fight against pandemics, too.

About the Author

Stuart RauchStuart Rauch

Stuart Rauch is a 25-year product marketing veteran and president of ContentBox Marketing Inc. He has run marketing organizations at several enterprise software companies, including NetSuite, Oracle, PeopleSoft, EVault and Secure Computing. Stuart is a specialist in content development and brings a unique blend of creativity, linguistic acumen and product knowledge to his clients in the technology space.

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