You’ve probably heard of big data before -- all that digital information about you that companies, governments, and organizations use to improve their services and market directly to you. What about the science and scientists who can drive it? Behind all that big data lies data science and the people who can manipulate it -- data scientists.
In a 2009 McKinsey & Company article, Hal Varian, Google's chief economist, said, “The ability to take data -- to be able to understand it, to process it, to extract value from it, to visualize it, to communicate it -- that’s going to be a hugely important skill in the next decades.”
It has been a hugely important skill and the world is already feeling the impact of big data, data science, and the work of data scientists.
What do they do? Data scientists identify and ask pertinent questions, collect large quantities of data from a variety of sources, and then organize and analyze it. They take their results and derive solutions to big problems, and share their findings in meaningful ways so that business can make data-informed decisions. All industries require this valuable skill set and the need for data scientists is on the rise.
Over the past decade, data scientists have proven their indispensability to businesses and have changed the landscape of major industries. The US Bureau of Labor Statistics reports, “As a group, mathematical science occupations are projected to far outpace the average growth rate for all occupations,” with some related to data science seeing an uptick in demand by as much 50 percent over the next 10 years.
Here are four industries that data science has revolutionized in the past decade.
Finance is no longer just about traditional numbers. It’s about code.
In every industry, the ability to make predictions is important. In finance, it’s critical.
In addition to bankers, stock brokers, accountants, and financial whizzes, Wall Street increasingly seeks data science experts.
What do data scientists do in the finance sector? They work in everything from predictive analytics, to customer management, to cloud-based software management, to fraud detection, to cyber security, to marketing. They have backgrounds in AI and machine learning and work on designing and analyzing algorithms that detect anything from malicious intent to how sectors of the population spend and invest their money.
In finance, data scientists who specialize in machine learning design and create complicated statistical models based on distillations from big data. The more data fed into the machines, the more accurate the algorithm, and the more refined the algorithm.
Many in the financial sector do not have the skills needed for data manipulation at this level.
Think about all the data the healthcare system generates on a daily basis: medical records, billing, patient management systems, provider management systems, and now personalized health information from wearable devices like FitBits. Where does all the data go?
In healthcare, the opportunities for data scientists are nearly limitless.
Perhaps data science’s biggest impacts on healthcare are in public health and reductions in healthcare costs. Lots of healthcare organizations have started to use big data from websites, wearables, social media, and Google Maps to understand population movements, health ailments, and medical results of people living in certain areas.
Data scientists can analyze billing and clinical systems data to determine how facilities and resources are allocated -- and how they might be better allocated to minimize losses, maximize patient care, and minimize patient expenses.
Healthcare’s newest field of predictive healthcare also has incredible opportunities for data scientists, as genetic testing and genomic sequencing take center stage in medicine. Used in conjunction with current medicine, predictive healthcare gives data scientists the opportunity to make positive impacts on the lives of individuals.
3. Environmental science
Ever think about your trash and recyclables?
Environmental data scientists think a lot about yours and everybody else’s too. In terms of positive environmental impact, data science is ripe with opportunities to improve the state of the planet.
A company in Edinburgh is taking a different approach with all of the environmental data available. According to Insider.co.uk, Edinburgh waste management data analytics firm Topolytics is working with Ordnance Survey to create a map that can track all of the UK’s garbage.
Specifically, the smart system will track over 20 million movement of waste from homes, local authorities, businesses, and construction sites from their original locations to their disposal or processing places. The Ellen MacArthur Foundation recognizes Topoanalytics as a leading “smart” waste company.
Data science has a place in other environmental science issues, too. According to the National Center for Ecological Analysis and Synthesis, there’s no longer a question of having enough data. It’s a question of what to do with it all. To work on answers, they initiated a six-month fellowship in Data Science to support two current real-world projects: the Arctic Data Center, part of the National Science Foundation, and the State of Alaska’s Salmon and People project. Both projects use big environmental data to help drive policy and education about the impacts of climate change.
Data scientists are changing the game for sports fans, too, especially when it comes to player recruitment.
Of course, it all started with Moneyball, the story of how Billy Beane and Paul DePodesta transformed the Oakland A’s to a winning team by looking at big data.
But the big data of the early naughts is different to the big data now. The implications are bigger, too.
Last November, Forbes reported that Blake Wooster of the UK’s 21st Century Club built a group of data scientists, software engineers, strategists, and management consultants to help football clubs find “competitive edges”.
He said, “The main thing a lot of people took from Moneyball is that there is a different way to measuring baseball than people knew about. The inspiration we took was that there are teams who can overachieve relative to their resources by thinking differently and having a differentiated approach.
He added, “Much like many industries are being disrupted by technology, analytics and new ways of thinking, that's what we're doing in football.”
It’s what a lot of industries are doing. Ready to take a deep dive into a career in data science?
Study Data Science at Bologna Business School
Bologna Business School offers an unparalleled Master in Data Science that gives students the skills and training they need to be data scientists in any industry.
The program focuses on amplifying students’ knowledge of big data and its analysis to prepare them for careers in senior management positions.
Over the course of two terms of classes in English and 600 work experience hours, the master’s program draws from three core competency areas: business economics, IT, and speculative analysis or statistical mathematics. Students use a variety of programming and analysis tools including open-source software.
In terms of career development, the Bologna Business School helps students puruse their career goals through career development sessions, advice, and one-to-one counseling. The school boasts a 91 percent placement rate for students who complete the full-time master’s just six months after graduation.
And that’s not all: the Bologna Business School offers 6,000 Euro and 4,000 Euro scholarships to the most deserving applicants.
Alumnus Elena Cipressi says, “This is an educational path which connects people, expands knowledge and improves your academic background; there are countless sources from which you can deduce the role of Data Scientist. This Master adds one more dimension: the human one, by giving everybody the opportunity to customize it with critical thought, thanks to the continuous interaction between students, professors and professionals.”
Ready to enter the frontier of data science? Then check out Bologna Business School’s Master in Data Science!