Big data examples: 6 Ways it’s transforming business

 

When the internet emerged in the early 1990s, some of the world’s most prominent minds began theorizing about what would later become big data. But it wasn’t until 1999 that the term first appeared in publication, gaining a more solid definition in the early 2000s.

“Big data” essentially refers to a collection of datasets so large that it cannot be analyzed with normal statistical methods. The Bureau of Labor Statistics explains that such data can include videos, pictures, maps, words, phrases and numbers. Customer reviews posted on a website, comments and photos logged on a social media platform, electronic medical records and bank records are all examples.

Professionals who work with big data have created ways to not only harness our surplus of data, but to also use it to transform how businesses operate. Consider these six big data examples that illustrate how business as we know it is changing.

6 Big data examples that are transforming the business world

Over time, more and more businesses have begun to collect and analyze big data. A 2015 global study revealed that about 90 percent of all companies think they could benefit from using big data.

“Global competitive pressures are creating greater necessity for data-driven business practices,” explains Dr. Monica Shukla-Belmontes, associate dean of corporate pathways and competency-based education at University of Massachusetts Global. She also adds, “This use of analytics will help businesses to better understand current trends, evaluate how to maximize operational opportunities and explore models to increase agile decision making.”

Below is a sampling of the many ways companies across industries are using analytics to improve their processes.

1. Expanding business intelligence

Business intelligence — a technology-driven process for analyzing data — has existed for a long time. But big data has enlarged the capabilities of business intelligence. Analysts can use data both to get an overview of the past and to look ahead.

With big data, companies can mine massive amounts of information, including findings from outside their own data sources. In addition to empowering the efficient capture and storage of large amounts of data, big data enables businesses of all kinds to analyze that data so that they can better understand their own operations. As big data is mined and analyzed, businesses are able to gain a more comprehensive view into their processes and gain valuable insights about their customers’ interests and behaviors. In sum, big data can streamline business intelligence processes and help businesses better address the needs of their consumers.

2. Enhancing user targeting

Big data has allowed for some pretty monumental changes in the ways businesses target their consumers. Big data makes it possible to analyze a user’s digital footprint and then use that information to create more targeted, personalized advertising campaigns.

Participating in today’s digital landscape means that most of our interactions with technology — our Google searches, our Tweets, our Facebook likes and comments — generate information that can be used to inform what ads are served to us on the platforms we visit. This helps organizations target the right advertisements to the right users.

But the heightened user targeting enabled by big data doesn’t just benefit businesses — it also improves the overall user experience. “Data analytics has enhanced the consumer experience by providing consumers with increased personalization of products and services tailored to their unique needs,” Dr. Shukla-Belmontes explains.

Companies can, for example, utilize GeoTargeting to learn about the locations or businesses a consumer has visited recently. If your historical location indicates you’ve made several visits to car dealerships, businesses can use this information to include you within the target audience for ad campaigns for a type of car, a particular deal on car insurance or opportunities for savings at local dealerships. 

3. Improving customer service

Implementing technology that uses big data means businesses can address customer service concerns in a timely matter through the use of things like chatbots – the artificial intelligence systems we’re accustomed to interacting with through virtual conversations, such as in a chat window when visiting a store’s website.

The combination of artificial intelligence and big data can enable today’s chatbots and customer service teams to learn about a customer’s recent or past experiences with their business. By collecting data on user behavior, businesses are given the ability to know exactly what a customer needs before they even request it.

Real-time big data analysis can help businesses examine customer accounts to identify one or two issues the customer may need help addressing. This empowers customer support teams to provide more helpful and knowledgeable customer service. Businesses can also leverage predictive analytics to proactively contact users who may face issues in the future.

4. Increasing efficiency and reducing costs

Big data is also used to improve operational efficiency. It enables businesses to gain insights by analyzing various data sources. When it comes to manufacturing, for example, big data allows companies to analyze things like production, customer feedback and product returns to determine the quality of production and overall profitability.

Predictive analytics can also be used to increase production efficiency when businesses reduce outages by anticipating future demands. As a result, big data also reduces the overall cost of operation for companies of all kinds in a number of ways — minimizing indirect costs, monitoring potentially costly cyberattacks and even in hiring the right job candidates, reducing employee turnover.

5. Influencing customer behavior

In addition to creating a better advertising strategy, enhanced user targeting can also be used to guide or nurture customer decisions. Big data can be used to analyze every individual action a customer takes when they land on a web page. By examining a user’s keystrokes, mouse movements and clicks, it’s possible to predict which moves they’ll make next.

By learning their customers’ behavior patterns, businesses better determine when to help point a user toward a sale or conversion. Using past behavior patterns in this way may mean customers become more likely to make a purchase.

6. Protecting against operational risk

Operational risk refers to potential loss related to human dependency and error. This includes things like fraud, computer hacking, reactions to catastrophes and failure to adhere to internal policies. Big data can help. When it comes to cybersecurity, big data enables analysts to examine, observe and detect irregularities within a network. This reduces the time it takes to detect and resolve an issue.

Big data utilizes two fraud detection techniques to protect against potential risks: statistical techniques and artificial intelligence. From matching algorithms to detect anomalies to using machine learning to automatically identify characteristics of fraud, big data has done a lot to help protect businesses in all industries.

Help fill the growing need for big data professionals

Big data’s growth has been nothing short of explosive. It’s no wonder that data science professionals are in such high demand. “Data scientist” has even been ranked as the top job in America for four years running.

If you’re fascinated by big data and you have a desire to fill the growing need for big data professionals, you might consider adding some data science skills to your business repertoire. Learn more about University of Massachusetts Global’s MBA in Business Intelligence and Data Analytics program for more information about the skills you could add to your resume.