A thriving economy solves people’s problems. No system is perfect and sound decision-making is critical to navigating a challenging world. Earning a master’s degree in data science gives analysts and data professionals the skills essential in a transformative new century.

We live in the age of big data, but without data management, analytics, and actionable insight, it is little more than a pile of bricks instead of the solid house it could or should be. “It doesn’t matter how much data you have,” writes Param Hegde in a Medium article. “What matters is what insight you are getting out of it.”

Data informs sound decision-making to the extent that it is effectively applied to real-world problems. The power of data, therefore, is unlocked by data scientists’ technical and analytical skills.

The value and demand for data scientists are commensurate with the rise of data as the lifeblood of businesses, organizations, and society. A data scientist’s role has never been more critical than now, though not as much as next year or the year after.

A master’s degree in data science clears the path to an exciting career in the public and private sectors. Let’s briefly explore how data science is critical to problem-solving, forecasting, and solving modern business challenges.

Time is Money; Data is Money

The saying goes that “time is money.” The corollary is that data is money. With data, problems are identified and solutions discovered. Wasted data is lost time and money. Data analysis saves time (and money) by safeguarding against ill-informed decision-making.

Leading through data analysis is both tactical and strategic. That leadership begins not with a complex algorithm but by first identifying a problem to be solved. Referring to our previous analogy, we must decide on the house that needs building before we collect the materials to construct it.

Technical and analytical skills are essential, but data science requires matching problems with the correct data. Once that match is made, the data “bricks” can be assembled, the house completed, and the problem solved.

The problems to which data science is applied flow through all aspects of our society, from movie recommendations to healthcare, banking and finance, energy, supply chains, manufacturing, and government. No sector remains untouched or can evolve without the tools and expertise of data scientists.

Predictive Analysis in a Rapidly Evolving Business Environment

Anticipating change and forecasting potential future pathways is critical in a disruptive economy. If the past few years have taught us anything, it’s that things can change on a dime.

Most have experienced this personally, but systemic change on the scale recently seen has arguably never before impacted so much, so many, and so substantially. Predictive analysis is the modern sextant used to navigate these choppy waters.

“This is the golden age of predictive technologies,” says an article in Business Standard. But that statement comes with a caveat. With the development of technology and “the resulting change in our ability to foresee potential future events has coincided with an exponential increase in the range and variety of possible outcomes,” the article states. “The same advances in technology that have enabled us to be more certain about our decisions have increased the complexity of the landscape in which those decisions take place.”

Leadership in an “age of disruption” demands adaptation at an unprecedented pace. Anticipating events, scenarios, and potential outcomes is critical for decision-making and problem-solving.

The Demand for Data Scientists

Digital transformation is the hallmark of the fourth industrial revolution. Organizations face challenges from all sides in an economy still sorting itself out from the global pandemic. At the same time, they must retool for a data-enhanced world.

Business leaders understand that a primary task for organizational and strategic success is finding and retaining the right talent. They realize that applied data analysis and communication is a mission-critical tool. Therefore, finding talented data science professionals is a priority for any successful, complex organization.

Salary figures reflect the level of demand. Glassdoor lists a median annual salary of $120,864 for a data scientist.

Filling the current skills gap and meeting future demand for data scientists in a whirlwind environment of change suggests that we not only need more data scientists but, crucially, more data scientists trained in the skills organizations need to stay competitive.

Data professionals have many potential avenues to upskill their talents. Earning a master’s degree in data science from a top-rated school is essential for meeting the most exciting challenges and helping solve the most significant problems we share.

Merrimack College Online Master of Science in Data Science

The online Master of Science in Data Science degree from Merrimack College provides professionals with the tools, conceptual foundation, and practical skills for leveraging data to solve business-critical challenges. The industry-aligned program allows motivated students to explore their full potential.

The newly redesigned, competency-based curriculum investigates six core data science skill sets and learning objectives, each reflecting the problem-solving methodologies of applied data science.

These skills and objectives include:

  1. Formulating Problems
  2. Collecting and Processing Data
  3. Analyzing and Modeling Data
  4. Presenting and Integrating Results into Action
  5. Real-World Applications of Data Science
  6. Capstone

Students complete six core courses and three electives. One elective must be from the Real World Application group. Each course is four credits for a program total of 32 credits. An expert faculty provides real-world experience and academic rigor.

Learn data-focused, problem-solving skills and help shape the future with a master’s degree in data science from Merrimack College.