What Covid 19 is teaching us about Big Data
Jan 11, 2021
Big data is an enabler. In the wake of the crisis, we have learned a lot about big data in action during the COVID-19 crisis. These lessons will make it easier for governments, enterprises, and vendors to deliver better big data projects and products. Visualization is paramount. With detection time measured in minutes instead of days, forecasters are forced to visualize every bit of data available. The success of the COVID-19 data management and response system created an ecosystem of companies that contribute to the program by providing specific expertise.
Covid 19 showed us the importance of real-time streaming analytics, and Big data projects are mission-critical and require high levels of collaboration across functional areas and agencies.
The virus has spread to every continent, and case numbers continue to rise. In 218 countries and territories, authorities have reported about 90.2 million Covid‑19 cases and 1.9 million deaths since China reported its first cases to the World Health Organization (WHO) in December 2019.
If you’ve been following the news of the COVID-19 pandemic, you likely realize how important it is to prepare for a global pandemic like this ahead of time. Enterprises and vendors alike have learned a lot about big data from this experience. Many in our industry speak up about how they have tons of data but no clue where to start on analyzing it. Visualization is paramount to get the most leverage from your big data. Big data projects need special consideration for three reasons: They are mission-critical and cannot fail, often the number one decision driver for many companies, and fail to deliver on the big data.
A great deal of analysis and knowledge sharing was needed to make sense of the hundreds of terabytes of data coming in from COVID-19.
Monitoring the health situation, trends, progress, and performance of health systems requires data from multiple sources on various health topics. A core component of WHO’s support to the Member States is to strengthen their capacity to collect, compile, manage, analyze and use health data mainly derived from population-based sources (household surveys, civil registration systems of important events) and institution-based sources (administrative and operational activities of institutions, such as health facilities).
Our success with CoVID-19 was mainly because we could integrate clinical data from a variety of sources.
Digital strategy in a time of crisis. Now is the time for bold learning at scale.
Governments around the world moved the timeline for digital transformation in the face of the coronavirus era with the luxury of time disappearing. From the first wave of the pandemic to the second wave, governments that once mapped digital strategy in one- to three-year phases must now scale their initiatives in days or weeks. But more important, time pressures will force organizations to be high – resolution planning and execution.
If the pandemic has made anything clear to governments and businesses, it is that this is no time for complacency. Companies in every sector and geography are racing to become ever more digitally agile to ensure they can capture new opportunities and avoid getting left behind by a fast-moving market.
While the pandemic is still evolving — and no one knows what will happen next — executives
already recognize some imperatives. To deliver a healthcare system that can efficiently treat, contain, and ultimately defeat the disease, governments must collaborate with the private sector to develop a rapid response force of data management systems that can track and monitor cases. Using COVID-19 data to fight & contain the pandemic with advanced analytics is critical to protect public health & save lives.
According to McKinsey, In one European survey, about 70 percent of executives from Austria, Germany, and Switzerland said the pandemic is likely to accelerate their digital transformation. The quickening is evident already across sectors and geographies. Consider how Asian banks have swiftly migrated physical channels online, how healthcare providers have raced into telehealth, insurers into self-service claims assessment, and retailers into contactless shopping and delivery.
A data analytics tool can show how countries’ different COVID-19 testing strategies and other mitigation methods can help reduce the spread of the virus.
The COVID-19 Data analytics tools demonstrate how recommended measures – such as mask-wearing, contact tracing, and social distancing – can work in conjunction with testing to reduce the spread of the virus further.
Many countries are using social distancing strategies to decrease the transmission of the virus before moving to full lockdowns. Using spatial data on human mobility, governments can see where measures are or aren’t working using dashboards and include critical POIs (hospitals, supermarkets, clinics) to understand patterns.
Social distancing strategies decrease the transmission of diseases among large populations. Their effects include discouraging travel, isolating infected individuals, and reducing public gatherings. Ethical concerns arise with quarantine measures, but a society faces the threat of an epidemic if it doesn’t take decisive action.
The COVID-19 crisis seemingly provides a sudden glimpse into a future world, one in which digital has become central to every interaction, forcing both organizations and individuals further up the adoption curve almost overnight. A world in which digital channels become the primary (and, in some cases, sole) customer-engagement model, and automated processes become a primary driver of productivity—and the basis of flexible, transparent, and stable supply chains. A world in which agile ways of working are a prerequisite to meeting seemingly daily changes to customer behavior.