Big data has made a big splash in plenty of industries in the United States. In fact, the data science field is one of the most rapidly growing industries, leading some to call it the sexiest job of the 21st century. But, why?

If you’re not a data scientist, the chances are the intricacies of data science elude you. However, you might be surprised at the myriad of ways data and computer science impact the world around you. Continue reading to learn about some of the industries and people who use data science.

Data Scientists

Being that this article is about who uses data science, it only makes sense to start with data scientists. Companies of all sizes extrapolate a lot of data from various data sources, and data scientists are the ones who help them make use of the data they gather.

Data scientists use data mining tools for data analysis that enable them to find correlations and anomalies between data sets. They’re the ones who extrapolate actionable insights from big data and use it to create data models, make predictions, and perform other business intelligence processes.

Data Engineers

Many data analytics processes take place using artificial intelligence and machine learning algorithms rather than human end-users. Data engineers design tools that extrapolate, format, and yield big data analytics so data analysts and business users can extract, analyze, and store data. Engineers create machine learning algorithms that fish the internet, databases, and other data sources for insights using formulas and scientific methods developed by data scientists.

Insurance Companies

The insurance industry is a game of risk. Insurance companies earn profits by getting more revenue through premiums than they pay out in insurance claims. Such being the case, they use analytics to get valuable insights into customer needs, make predictions, and create different insurance packages.

One of the greatest data science innovations is predictive analytics. Predictive analytics enables insurers to predict the probability that a specific applicant will file a claim on their insurance policy within a given amount of time. Using advanced analytics, insurers save money for safe drivers by either charging reckless drivers more for coverage or denying them coverage altogether.

Manufacturers

The manufacturing industry is one of the areas of business that’s most reliant upon big data analytics. When you’re in an industry that lives and dies on supply and demand, it pays to know what’s coming before it arrives.

One of the many ways in which manufacturers use big data is to forecast changes in customer demand. By using real-time data to stay up-to-date on customer preferences and behavior, factories stay on the cutting edge of product development, which is shifting towards product customization.

Web Servers

Have you ever noticed that advertisers these days seem to know exactly what products specific customers desire? Modern data science developments like cookies use artificial intelligence to collect data from web surfers and use their information to create targeted marketing campaigns. So, it’s no coincidence that when you’re on social media, you always see AirBnB ads for the places you would most like to visit. That’s because the web servers and search engines have eyes, and they use data science to learn what you like.

Customer Support

One of the greatest uses for data science is customer support. With time, companies have learned that there’s nothing more important to their success than the customer experience.

Interactive voice response and facial recognition are deep learning data science tools that provide end-users with an added level of biosecurity for their online information. Furthermore, customer support personnel use data science to personalize customer interactions and help online and phone line users get the solutions they need quicker.

As you can see, data science helps business leaders make better business decisions, predict future outcomes, and much more. Given the many industries that utilize big data, it may be easier to answer the question, “Who doesn’t use data science?”