Big Data and its Impact in the Post Pandemic World

01 July 2021

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“Hiding within those mounds of data is knowledge that could change the life of a patient, or change the world.” — Atul Butte, Stanford University

In combating the coronavirus pandemic, big data has been invaluable in understanding patterns in the spread of the virus. It has also helped track the virus in populations, even down to the level of cities and neighborhoods. In addition, big data has assisted with strategic planning and decision-making to predict and anticipate future pandemics.

The coronavirus pandemic accelerated the growth of a lot of digital processes. As a result, several businesses worldwide have been forced to quickly ramp up their digital strategies to survive the new world of virtual business. This acceleration has also led to a further explosion in big data, its usage, and how value can be derived to help businesses forge ahead in this post-pandemic world.

What exactly is big data?

To define big data, we need to understand what data is. Data are units of information, often numeric, that are collected through observation. Big data refers to data that is huge in volume yet increases exponentially with time. It is generated on an enormous scale, and it can’t be stored or processed by any traditional data storage or processing units. Big data can be characterized as data with the following features; volume, variety, and velocity.

Data has been defined as the resource that will power the internet economy, power the future, power our lives. It’s why people say the more data you have, the more powerful you are. In some ways, I agree with this. I think the scale of data over the next decades will be one of our most important resources.

What value does big data bring right now?

What makes big data valuable is that it is data about different things. It isn’t just that it is made up of numbers; it’s data about human behavior, it’s data about our health history, it’s data about our spending patterns, it’s data about our daily lives.

Before the big data era, businesses assigned relatively low value to the data they collected that did not have immediate value. With the big data era, this investment in collecting and storing data for its potential future value changed. As a result, businesses made a conscious effort to keep every potential type of data. With big data, businesses can now predict their customers' needs, behavioral patterns, pain points, and future complaints. The implications are huge.

Netflix used big data to design the success of the popular show “House of Cards.” Massive amounts of user data collected over the years were used to drive the show's creative direction. So strong was their confidence in the show’s success that they signed off on 2 seasons before the pilot episode. A $100 million vote of confidence because of big data.

Financial institutions still depend on the credit score, credit history, revenue, and banking transactions of users to determine whether they are creditworthy. This is exactly where big data can help, as its application goes far beyond the user's data. For example, loan decision systems are taking help from machine learning to observe the patterns and behaviors that help financial institutions to determine whether a user can really be a good credit customer or not. As a result, big data and machine learning make credit decision systems more accurate and reliable.

How will businesses thrive in this new world?

For the third consecutive year, investment in data and AI initiatives has been nearly universal, with 99% of firms reporting investment in data and AI, according to findings from a newly released executive survey from NewVantage Partners.

How will businesses thrive in this new world? By strategically investing in big data and also better data. Data is the raw material of artificial intelligence and machine learning. It is the connective tissue of any digital organization. For big data to deliver value, it needs to be usable; data quality is essential. Businesses need clean, machine-digestible data labeled to train machine learning models with the help of subject matter experts. They require a data storage infrastructure that transcends functional silos within the business and can deliver data quickly and efficiently.

The use of big data has accelerated since the onset of the global pandemic, and there are several lessons to be drawn from the coronavirus pandemic. Perhaps, one of the most critical is the importance of using data to prepare for potential scenarios and enhance our decision-making. Example Image