Technology

Big Data Is Changing Our Lives For The Better — Here Is Why

When we discuss ‘big data,’ we refer to the amount of information that is always being generated. Think about how many people are born every day. That is a new set of information for a new set of records. When you register for a new online account, make a purchase, or even visit the doctor — you are adding to this big data.

It is unstructured, and it is always growing. Mind-blowingly, there are said to be more than 44 zettabytes of data out there right now. To put that into perspective, a single zettabyte is a billion terabytes. A single terabyte holds enough data to house a thousand encyclopedias!

If you are studying for a master’s in data science (such as at Baylor University), you will likely come across big data as a core concept early on. It refers to the ever-expanding information pile that is growing all around us.

It is staggering to consider just how much data is growing. However, it does not have to be scary. In fact, we are already using big data to our immense advantage in everyday life. Let’s look at a few examples.

Big data and healthcare

Data is crucial for keeping healthcare services running. Without it, our doctors and nurses would struggle to find adequate treatments for millions of unwell people all over the world. Moreover, big data is helping healthcare providers to find new ways of managing expectations and planning for resources.

The COVID-19 pandemic brought into perspective just how much pressure global healthcare is facing. Without big data, it is impossible to plan for the challenges the industry is likely to face in the coming years.

Collecting and analyzing big data helps healthcare professionals to plan out treatment solutions and space to help people who need specific types of care. Ultimately, by analyzing how many people use specific services or have a given condition, our hospitals and surgeries can better plan to offer greater care and support.

Big data and retail

While your everyday shopping experience may not feel like it has changed much over the years, big data has helped retail operations to better plan for sales management and marketing.

For example, data captured from willing customers gives clear images of what managers can expect from sales periods, which products sell best to which audiences, and where they should place the most focus on merchandising and advertising.

Big data was not available to retail executives decades ago. Much of the ‘golden age’ of advertising and mass-market planning was based on traditional customer canvassing. While these processes are still highly useful today, big data management and analysis help retailers make more confident decisions when planning.

Furthermore, consider how many ‘channels’ shoppers can use nowadays. They no longer need to depend solely on physical shopping to satisfy their daily needs. Some retailers look closely at big data available through app use and online browsing and connect them to journeys their customers take in-store. It can be complex — but it drives revenue and more satisfying customer experiences.

Data handled in this way will always need a trial-and-error approach. It is why software testing, alongside big data handling, remains so vital.

Big data and education

Big data is proving extremely useful in helping educational bodies plan for students’ needs in the semesters to come. For example, student data such as exam grades, lesson attendance and basic demographic data help to build clear averages on how their teachers are performing.

This data helps colleges, schools and universities fine-tune lesson plans, modules, and even marketing. For example, they may find that their students typically graduate highly in a given subject — such as math — which may lead an institution to promote itself as a math college.

Big data is great for helping educators dive deep into how their teaching methods actually perform. While they had previously relied on student scores and employment records to measure effectiveness over the years, big data allows these institutions to look carefully at specific drivers for success.

What is it about a specific teacher that appeals to students? Do they learn better from home or in class? How long should classes be to provide the most support to young people? These are just a few example questions that big data, when analyzed and handled efficiently, can help to answer.

Big data and disaster management

Intriguingly, big data is also proving highly useful in helping us predict and plan for various natural disasters. By correlating and analyzing information from historical earthquakes, hurricanes, floods and more, local authorities can plan for future problems with greater confidence.

By using big data, authorities can develop early warning systems to monitor a variety of concerning weather patterns. These systems can then provide greater reassurance to people in local areas. It is also highly useful in developing predictive models beyond basic weather forecasts.

However, it does not start and end being useful at predictions alone. Big data is also immensely helpful in monitoring real-time disasters, tracking potential spread, impact, and where a given weather condition may be moving next.

Crucially, monitoring big data also allows authorities to carefully distribute resources and support to areas that need them the most. This may include food, water, emergency care and medical supplies. 

After a disaster passes, authorities can analyze big data to help plan for similar problems occurring again in the future. What were some of the challenges they faced? How could they have better planned for this issue were it to happen again?

Conclusion

Ultimately, big data is helping us become more efficient in everything we do. Not only that — but it is proving useful in creating more satisfying shopping experiences, ensuring we get help at school, and even helping save lives in natural disasters.

As data grows and builds, it is safe to say its usefulness will too. We are constantly finding new ways to track and manage information and ways in which we can better predict events to protect communities.