Data science is changing the world. Once a relatively small academic field, this discipline has exploded across the globe thanks to the rapid digitalisation and technological growth of, well, everything. Today, the uses of data science span every industry imaginable: in medicine, epidemiology, business, research, development, logistics, and countless other fields. Let’s take a look at some of the best examples of how data science is changing our world forever, and why it’s such an amazing in-demand and high-paying career path to get into.
In the 1990’s the Oakland Athletics baseball team didn’t have the budget to sign leading players. At the time, players were picked on face-value assessments and the talent scouts’ individual ‘hunches’. With the introduction of sabremetrics, the team’s general manager Billy Beane and his assistant Paul DePodesta started picking unconventional or unpopular players based on their average performances. The team they picked went on to win 20 games in a row, breaking league records and cementing the credibility of data science in sports (and eventually spawning a movie about the events, called Moneyball).
Today, sports analysis is a billion-dollar industry, with partnerships between some of the biggest teams and players, and the largest tech corporations – such as Real Madrid and Microsoft. The uses of data science and analytical tools in sport analysis include understanding performance, improving training, and predicting competition outcomes. These applications are also widely used in the multi-billion-dollar sports betting industry, which uses data science to create fair odds for gambling.
Investment and better business
There’s a lot of money to be made in trading stock and shares. The thing is, if you’re too slow, you’ll miss out on great opportunities and immense profits.
When it comes to doing something over and over again, at an extremely high speed, human traders just can’t keep up with computers. The financial markets and investment have been revolutionised by algorithm-based trading, allowing speeds of trade that are simply impossible for humans. This is one of the key uses of data science: not just to make better investment picks, but also to automate those investment decisions to beat your competition (where even a microsecond of advantage can mean millions of dollars).
It’s not just investment that data science makes easier, faster, and better: it’s just about every other business too. Data-driven integrated solutions make business more efficient and less expensive – which directly translate to better profits. Stock management, product analysis (to figure out which products to promote and which to discontinue or improve), and supply logistics are just a few of the hundred uses of data science in business. It’s also vital for efficient, high-quality customer acquisition and marketing, so that you don’t blindly dump millions of dollars into ineffective marketing campaigns.
The improvements that data science can make to business can seem insignificant and counter-intuitive, but they result in large improvements over time. UPS saved 10% in average annual fuel costs by telling your delivery trucks to avoid left turns, and a shipping company saved millions in annual fuel costs by implementing a machine learning algorithm that adjusts engine power of ships according to weather, ocean currents, the pitch of the ship, and wave action to adjust it’s engine output.
The medical industry is where data science is most vital. Hospitals and healthcare systems have millions of users with complex histories, backgrounds and needs – overseeing these records in a safe and efficient manner is key to improving the privacy and health of the patient.
However, data science is used in more than just simple administrative management. Detection, diagnosis, and treatment of hundreds of different diseases are important uses of data science, and they actively help to improve the health and lives of thousands of people.
Medical uses of data science:
- Imaging – detecting things that a doctor might miss in magnetic resonance imaging (MRI), X-ray, computed tomography, mammography, or other scans, especially when scans are poor-quality. Already, deep learning algorithms are beating expert radiologists at detecting signs of breast cancer in mammograms.
- Drug discovery – machine learning to predict useful compounds and to simulate their effects without needing physical testing.
- Monitoring patient health – heart rate, blood pressure, temperature, insulin levels – these are all things that can tell a doctor a lot about a patient’s health and progress. With wearable detection devices and data science, the doctor can tell how the patient is doing in real time, or even detect problems before they become serious.
- Detection and diagnosis – with data science, doctors can predict and start treating illnesses before they become serious. For example, in India the L V Prasad Eye Institute uses Microsoft’s machine learning technology to detect and prevent reduced vision and blindness. Similar techniques are used in the United States to identify the early signs of diabetic retinopathy and treat them so as to prevent blindness.
- Epidemiology and large-scale health management – By now we’ve all seen one of the many hundreds of online tools that track COVID-19, breaking down total numbers of cases, infections, recoveries and deaths. Tracking and controlling the spread of deadly illness over large areas (even globally) is one of the most important uses of data science in modern times.
Limitless research applications
Data science is so open-ended and limitless that it can be used for a seemingly infinite number of applications in computer science, research, law, entertainment – and just about whatever else you can think of.
Here are a few of our favourites:
- An AI that automatically challenged and overturned 160,000 parking tickets in London and New York.
- An AI that creates new music, with instruments in a range of musical styles, including rudimentary singing.
- AI that can look at visual images and actually use it: sorting graphs, completing sequences and maths problems, and even recreating PacMan as a playable game using just a few images.
- An AI that turns your rough sketches of landscapes into realistic scenes.
- An AI that can detect and reconstruct sound waves from video, like something out of a spy movie.
Are you interested in learning how to use data science, algorithms, and machine learning to unlock huge profits, improve your business, or fast-track groundbreaking research? Our Data Scientist bootcamp teaches you everything you need to know to get started on seeing, managing, and using data for a wide range of applications. Start your career in data science by signing up for our free trial here.