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Keys to Managing Real Time Data During COVID-19

n this special guest feature, Ben Schein, VP of data curiosity at Domo, draws on his many years of experience with real time data working at Target during the days of Black Friday to the current day where he works to monitor a new COVID-19 tracker. There is something very powerful and culture changing about being connected to your data (and by extension your customer or constituent or patient) in real time.

The Data Governments are Using AI to Fight COVID-19 in Africa and Asia

Fraym is using artificial intelligence and machine learning to help aid organizations in Africa and South Asia identify populations at risk due to Covid-19 using new geospatial visualizations.

COVID-19: The Great Artificial Intelligence Accelerator

In this contributed article, Ramayya Krishnan, Ph.D., the W. W. Cooper and Ruth F. Cooper Professor of Management Science and Information Systems at Heinz College and the Department of Engineering and Public Policy at Carnegie Mellon University, discusses how history shows, COVID-19 is likely to further reinforce the profound impact technology and AI have on our daily life. As long as we can collectively prepare for and embrace this reality – all indicators point to a promising future.

Did Big Data Fail Us During COVID-19?

In this contributed article, tech blogger Caleb Danziger observes that governments and organizations across the world have employed big data to respond to the COVID-19 crisis. Some continue to sing its praises, but should that be the case? How has the world of big data affected the fight against coronavirus?

Healthcare Hit by Data Tsunami

In this contributed article, David Leichner is CMO at SQream, discusses how healthcare organizations are waging battles against cancer, diabetes and heart disease while also struggling to beat the COVID-19 pandemic. Despite the fact all of these illnesses have different symptoms and causes they all have something in common. Big Data is being fed into models that can find potential treatment and cures.

Three Ways Data Scientists are Fighting COVID-19

Data scientists in academia, non-profits, and the government have come together to track and respond to the economic & humanitarian impacts of the coronavirus. Put together by our friends over at SafeGraph, here are three ways data scientists are fighting COVID-19.

Accounting for the Unknown in the Time of COVID-19: How Data Scientists Can Adapt

In this special guest feature, Jonathan Prantner, Co-founder & Chief Analytics Officer at RXA, discusses how given the fast-paced nature of the world right now, data scientists working to understand and predict business impact will need to adjust current models or build new ones to make sense of COVID-19.

Prioritize, Don’t Ration: AI Will Lead Healthcare through the Post-COVID Bottleneck

In this contributed article, Ohad Arazi, Chief Executive Officer of Zebra Medical Vision, explains that while AI can’t yet fight the coronavirus directly, it can play a central role in creating the efficiency needed for healthcare professionals to get to as many cases possible, especially post-COVID-19.

How Data Collection During the Country’s Reopening Can Accelerate Return to Normalcy

In this contributed article, Sheldon H. Jacobson, PhD,, Founder Professor of Computer Science at the University of Illinois at Urbana-Champaign, is an advocate for advanced-analytics-based modeling to monitor the spread of COVID-19. Every state reopening represents an opportunity to collect data and identify best practices that can benefit other states.

Insights Beyond the Bedside: Machine Learning for Healthcare Administration, Utilization, and Cost (AUC)

In this special guest feature, Corinne Stroum, Director of Product for Utilization and Cost at KenSci, discusses how healthcare’s migration to electronic medical records in the early 2010s heralded an age of promise: increased efficiency, an opportunity to understand disease and populations at scale, and a reduction in errors. Like other industries, healthcare has also faced the challenge of adopting technologies before policy and ethics have had a chance to understand its implications.