What is Data Science?
Data Science is the practice of using computer science and other disciplines to discover meaningful insights from vast amounts of data to solve problems, create more efficient systems and predict future trends. In a world where big data touches every part of our lives, there is a growing need for data scientists who can find innovative ways to collect, analyze and visualize data and effectively present their findings.
Many associate Data Science with how it’s used to target online advertising for Google or Facebook, handle logistical networks for Amazon, or manage the complexities of gig-economy businesses like Uber. But Data Science is being used in more ways than you might expect. Today, Data Science is used to:
- Manage and improve transportation routes to reduce carbon emissions.
- Find future sports stars and assemble winning teams.
- Create personal healthcare recommendations.
- Identify and predict disease trends.
- Reduce tax fraud.
- Predict and prevent crimes before they occur.
Data Science Fields
Data Science is an interdisciplinary study that combines computer science with elements from the fields of mathematics, statistics, psychology, social science and expertise in a wide range of industries. There are several areas covered through the Master’s in Data Science offered through Drexel’s College of Computing & Informatics.
Artificial intelligence (AI) and machine learning are also playing a growing role in Data Science, which is why we offer a Graduate Certificate in Artificial Intelligence and Machine Learning for Data Science.
Data Science Industry Trends and Career Opportunities
The need for data scientists spans a variety of industries that range from technology and finance to telecommunications and market research. As more and more companies attempt to harness the power of Big Data to make more informed business decisions, the demand for jobs that place a focus on Data Science will only increase.
The median base salary for those with a Master’s Degree in Data Science is $97,579 according to Payscale; they have the potential, however, to earn more depending on their level of experience. Professionals with a Master's Degree in Data Science stand to make up to 36% more than others in the predictive analytics field.
And the need for qualified data scientists will expand dramatically. The US Bureau of Labor Statistics predicts that occupations associated with Data Science will grow by 31% in the next ten years – one of the top 20 fastest growing professions in the country, because:
- As global competition increases, businesses need to find new ways to drive efficiency, improve profit-margins and target customers with greater precision. Data Science is a growing part of the decision-making process for businesses of every size.
- As self-driving vehicles and other automation-based technologies develop, Data Science will be at the heart of the technologies that make it possible.
- As the challenges at the heart of medical and scientific research become increasingly complex, Data Science will be needed to spur new innovations and produce life-saving medical treatments with greater speed and safety.
- As environmental issues affect our world, Data Science will play a critical role in preventing the spread of new pandemics, protecting people from the adverse effects of climate change and finding better ways to manage and preserve our natural resources.
What Do You Learn in Data Science?
To navigate the complexities of how Data Science is used in different fields, successful data scientists must understand these four key components:
- Data Component – Using the correct methodologies to collect, manage and encode data to make it ready for analysis and visualization.
- Algorithm Component – Creating descriptive, predictive or prescriptive algorithms to analyze and visualize the collected data.
- Real World Component – Understanding how the data visualization and analysis can be combined with real-world expertise to achieve the desired results.
- Ethical Component – Maintaining the standards required to avoid bias and ensure that results are reported and presented honestly to stakeholders.
Combining these components allows data scientists to meet the challenges of an increasingly complex world.
Students of Data Science learn how to use data mining, visual analytics, artificial intelligence and other innovative technologies to collect, organize and visualize enormous amounts of data from a wide range of sources. Students then learn to find hidden trends and insights and use them to recommend and implement a course of action. Students also learn how to ethically manage and present information to avoid biases that can skew their results and how to effectively present results to key stakeholders.
Because Data Science is interdisciplinary, it provides opportunities for students and professionals with training in statistics, mathematics and social science as well as computer science. If you’re an undergraduate student or adult learner, we encourage you to learn more about the Bachelor’s in Data Science available through the College of Computing & Informatics. If you have training and a professional background in these disciplines, you may want to consider a Master’s Degree in Data Science.
Through Drexel CCI’s industry-aligned curriculum and unique, hands-on capstone project, students are empowered to build robust foundations for career and professional development, while maintaining a high level of academic achievement. Successful students emerge from the program equipped to become pioneers and leaders in a diverse array of rapidly-growing global industries.
What Career Can You Have with an MS in Data Science Degree?
What is a data scientist and what does a data scientist do? Data scientists use an array of tools and methodology to analyze and interpret data. They weave together statistics, machine learning, and critical thinking processes to interpret data and extract deeper insights.
Through a rigorous course of study at Drexel’s MS in Data Science program, students develop a comprehensive and competitive skill set, enabling graduates to explore an exciting range of Data Science career paths.
Potential jobs after obtaining an MS in Data Science include:
- Business intelligence specialist - A business intelligence specialist collects and evaluates data -- such as internal, industry-wide, and competitor data -- to help businesses take advantage of market trends more successfully.
- Data analyst - Data analysis is the practice of assessing and correlating data (including expenses, sales, social factors and more) to deliver actionable recommendations to businesses.
- Data engineer - Data engineering involves collecting and processing information, developing databases, and performing system maintenance, among other roles.
- Project manager - Project management is a leadership role that involves strategically planning and carrying out a wide array of business projects, accounting for factors like budget, timeline, and objectives.
- Statistician - A statistician collects and presents various datasets in order to help businesses make better marketing and budgetary decisions. Statisticians sometimes serve as consultants for other companies.