Why Is Big Data Big Business?

The large-scale collection and analysis of information guides organizations. The business world is undergoing a revolution generated by big data. In 2001, data analyst Doug Laney coined the term “The 3 Vs” to describe the defining properties of big data: Volume, Velocity and Variety. Volume refers to the amount or scale of data; Velocity refers to the speed of data processing; and Variety refers to the diversity of data — from “likes” on Facebook to credit transactions. These three Vs have since been added to, reflecting the complexity of today’s data ecosystem, with Veracity, Value and Variability rounding out the new “six Vs of big data.”

While the term “big data” is relatively new, the collection and storage of large amounts of information for targeted analysis existed long before the internet came into being. The U.S. was once the largest contributor to global data, but emerging markets are growing at a rapid pace, and the vast amounts of data created and stored are almost unimaginable.

Big data is big. According to The Small Business Blog, the estimated amount of data produced every day in 2023 is roughly 3.5 quintillion bytes. This includes everything from data from NASA to photos on Instagram. Many experts expect the amount of data created and consumed annually to top 180 zettabytes by 2025.

However, the vast amounts of data that businesses collect matter little unless they can process and understand the information. Data is only useful when organizations can derive value from it through applying data analytics methods and tools to process and understanding information, make connections and extract insights. Big data is big business when the facts gained from analysis offer guidance to decision-making.

This intersection of data analysis and managerial processes is the focus of the University of Southern Indiana (USI) online Master of Business Administration (MBA) with a concentration in Data Analytics. The degree program’s in-depth studies prepare graduates to lead their organizations through effective data management and data-driven decision-making. It’s imperative that today’s businesses align their big data programs to their business objectives to stay competitive by becoming more efficient, proactive and predictive.

Who Uses Big Data?

Some people think that data collection is all about secret government agencies sifting through our emails, looking for illegal activities, or worse yet, marketing companies looking to sell us more products. Though real, these examples are only a small part of the story. Many industries use this data to make our lives better.


While big data is utilized in healthcare in the same way it is in retail and manufacturing — to improve profits and cut waste — it’s also being used to predict epidemics, improve quality of life and avoid preventable deaths. Data drives rapidly changing treatment options in healthcare. Data analytics helps healthcare professionals analyze patient patterns and predictively highlight warning signs of serious illness. This can aid in the early identification and more effective and efficient treatment of medical problems.

Further, advanced healthcare analytics can potentially identify future health problems before they happen. Collecting data from various sources for a more comprehensive picture can help medical professionals recognize problems before they occur, giving doctors more information and therefore better insight into individualized patient care. This informs preventative care, patient education and much more.

Retail and Manufacturing

The way businesses buy and sell continues to evolve at breakneck speeds. In the retail and manufacturing sectors, collecting and analyzing data directly affects the innovation of products and services. The proliferation of e-commerce and social media has become a dynamic source of information on customer behavior, providing insights that drive innovations in products and services.

Retailers analyze data to predict trends, forecast demand, optimize competitive pricing, design marketing strategies and optimize supply chain and logistics processes. Data also drives improvement in the customer experience, customer service and personalization. For instance, some retailers have found the demand for books increases in the winter months, so some online retailers increase the number of book recommendations on social media and even target regions where temperatures are dropping.

The largest retailer in the world, Walmart, built one of the world’s largest hybrid clouds, capable of integrating public, private and edge cloud data to track millions of daily transactions, allowing the retailer to respond to market changes in real time. Demand for products by geographical area can also be leveraged, preparing goods and readying shipping before customers even place an order.


The use of data in the education sector has exploded in recent years, with all segments of education mining data to improve services. Local school districts use data for everything from planning bus routes to tracking discipline and academic achievement. Schools use data to gauge lunchroom preferences and improve classroom cleanliness. Teachers can even analyze data to learn what types of classroom instruction are most effective.

On a larger scale, data collected from Massive Open Online Courses (MOOCs), which deliver education to millions via the web, provide tremendous insights into academic success and the student learning experience. AI-driven analytics software can evaluate and predict student satisfaction even when student feedback is limited or difficult to quantify. Educators can now analyze data gathered from millions of MOOC students around the world to understand how people learn — and why learners fail.


As local and state government agencies apply analytics to their data, they can make substantial improvements in many areas, including managing utilities, overseeing agencies, refining public services and preventing crime. This directly affects the quality of life for all citizens. It also serves to highlight the diversity of data analytics career applications from the private sector to government agencies and nonprofit organizations.


Even though financial institutions utilize banking data to improve customer satisfaction, they also use it to reduce risk and fraud while meeting regulatory guidelines. One of the major causes of the last recession was the lack of transparency. Financial deals were based on relationships and personal opinion, not real facts and figures. Big data allows investors a more transparent view of markets and conditions, lessening the possibility of fraud. The banking industry, more than any other sector, has the responsibility to protect individuals’ privacy and manage risk, and big data is leading the way.

How Does Big Data Affect Business?

Analyzing data can aid an organization in many ways. While businesses can look to data to refine their internal processes, they can also use it to:

  • Reduce costs
  • Save time
  • Spur new product development
  • Prevent fraud
  • Gain business advantage on competitors
  • Expedite decision-making
  • Improve the customer experience

The potential for businesses to collect and analyze targeted data will continue to increase across all sectors of industry as the amount of data continues to grow. This information will affect business and marketing strategies as organizations learn what products customers want, who will buy them and what they are willing to pay.

What Is the Future of Big Data for Business or Global Economy?

As data mining technology continues to evolve, organizations must learn how to interpret the insights to best use the information. The era of big data will fundamentally alter many organizations, leading them toward information-driven business models. As the collection and analysis of big data continues to increase, it will significantly impact not only business and industry but also societies across the globe.

Learn more about the USI online MBA with a concentration in Data Analytics program.

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