Forbes calls data "the oil of the fourth industrial revolution." That's an apt comparison: it's the power source without which the rest of the revolution is possible.
Data science and analytics have shaken up the worlds of finance, medicine, business, and government, culling useful information from the 2.5 quintillion bytes of data created every day by 4.66 billion internet users. Data analysts help organizations identify problems and make important decisions about which investments to make, which products to develop, which markets to explore, and which customers to target.
"Gone are the days when traditional financial reporting, such as the profit-and-loss statement, balance sheet, cash flow, and simple variance analysis are enough," says EY (formerly Ernst & Young), one of the world's Big Four accounting firms. "Business leaders are now looking for in-depth insights that allow them to connect business activity to long-term value, model scenarios in real-time, and efficiently allocate resources."
In medicine, data science and artificial intelligence allow medical personnel to focus more on personalized patient care and improved efficiency and profitability. "AI frees up doctors and other healthcare professionals to focus on the patient, where momentarily they are spending 75 percent of their time analyzing data and doing paperwork," says Patrick Bangert, VP of AI at Samsung SDSA, which specializes in enterprise software solutions. "Patients have to wait four to six weeks, unaware of the results of a biopsy. If those are available instantly the treatment can begin sooner, leading to better outcomes."
In business, Mastercard teamed up with Google to track retail sales based on transactions. "This shows that Google's collaboration with financial services players is raising the bar for a new, innovative way of working," according to the Accenture Banking Blog. "An understanding of the right data sources can drive new product design decisions."
The U.S. government made a $10 million investment in data storage in 2021 "to consolidate their data analytics infrastructure into a single, flash-based storage system that will support the needs of grand-challenge data science," according to VAST Data, the creator of the storage platform. The upgraded system should "unlock the secrets hidden within vast reserves of biological, population and health data."
You can be part of this revolution… if you have the skills, training, and credentials. A Master of Science in Data Analytics program offers all three. What will you learn in a data analytics master's program? This article answers that question. It also covers the following topics:
A decade ago, Harvard Business Review called data scientist "the sexiest job of the 21st century." Ten years on, that assessment still holds, as data science and analytics continue to break new ground and open new career opportunities.
Who hires people with data analytics degrees? A study by Burning Glass, IBM, and the Business Higher Education Forum found the most job openings in:
Regardless of the field, most data analytics jobs share a few common requirements, according to Talend, a company that provides cloud data integration and integrity solutions for organizations. They include:
Carl Howe is director of education at RStudio, which provides open-source and enterprise tools for use with the R programming language, a key analytics tool. He spoke to Talend about the importance of getting into the weeds when it comes to data: "One irony of both data science and analytics is that while you need to know a great deal about models and machine learning, you could spend a great deal of your time cleaning real-world data before you analyze it. It's the old story of 'garbage in, garbage out.' You need clean data to work with before you can model it."
Job prospects in data analytics include:
Not only can a master's degree in data analytics open career doors, it can also enhance valuable skills that extend beyond your profession. These include problem solving, communication, and leadership, according to SAS, a developer of analytics tools. If you're intellectually curious, know something about programming, and have strong math skills and an analytical mind, this could be your field.
We've already looked at some of the big-picture lessons you'll learn while earning a master's in data analytics, such as problem solving, communication, and telling a story with numbers. Master's programs offer a mix of hard and soft skills.
At Butler University, for example, students learn "technical skills, like predictive analytics and effective visualization techniques, and enhance their soft skills, like critical reasoning and ethical decision-making, through an interdisciplinary curriculum."
Let's take a deeper dive into the broad spectrum of coursework you can expect.
First, the tech side. In addition to fundamental data analysis classes, expect to take such classes as:
If you specialize in business analytics, classes may include:
Some schools offer a health data analytics concentration with courses like:
Other concentrations include statistics, management, artificial intelligence, data engineering, digital retailing, and computational data analytics.
Then there are electives that help deepen your data analytics skills. Sample courses include:
Many schools require completion of a hands-on capstone project, such as working with a team to solve a business problem or creating a technical work proposal.
Requirements vary from school to school, but the following are common:
Online master's degree programs abound, offering part-time and full-time options and typically taking two to three years to complete. Here are a few of the many universities where you can obtain a data analytics master's degree from the comfort of your own hometown:
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