May 6, 2022

Data analysis involves taking raw data from one or more sources, cleaning it, curating it and ultimately applying analytic techniques to it designed to derive useful insights from that data. Those insights enable organizational leaders to make data-driven decisions and understand which areas they need to focus on to achieve strategic goals. Leveraging any and all available data is increasingly vital because decisions driven by facts are more likely to be strategically sound than those based on intuition or assumptions.

Many sectors and organizations are already reaping the benefits of having data analysts on staff. For example, the Securities Exchange Commission (SEC) uses data analytics to monitor activity in the financial market, which allows them to identify and catch illegal trading activity. Streaming services use data analytics to recommend content for consumers based on personal use history and broad user preferences. Researchers in the healthcare sector are even using data from wearable devices and other sources to make leaps in evidence-based medicine. 

Data analysts interface with data to uncover the most critical information, draw logical conclusions, and refine their findings into compelling narratives leaders can use to make business decisions. Analysts work in various industries, including finance, education, government, and manufacturing, but they utilize the same skill sets in all of them.

If you’re looking for ways to advance your career or are intrigued by the potential and power of data, you might consider pursuing an advanced degree such as the Master of Science in Data Analytics offered by Butler University. This degree provides data professionals with the interdisciplinary skills to tell stories and drive change using data. This article discusses the impact of data analytics, why professionals pursue this degree, and the job outlook for analysts with advanced education.  


One of the most significant outcomes of recent technological disruptions is a massive uptick in data generation. In 2017, the volume of data generated globally was 26 zettabytes. For context, one zettabyte is 1021 or 1,000,000,000,000,000,000,000 bytes. This number will grow to more than 180 zettabytes by 2025.

This data primarily comes from multiple digital sources–essentially anything that makes its way into a computer system, such as user histories, transaction records, or sensor logs. But due to a massive shortage of qualified data analytics professionals, much of this data remains unexplored. According to a joint Seagate and IDC study, “only 32 percent of data available to enterprises is put to work. The remaining 68 percent is unleveraged.”

Part of the reason for this discrepancy is that the amount of available data has grown far faster than the workforce necessary to make use of it. Modern data analytics is also a technical field with a high bar for entry. So while many organizations do rely heavily on data to drive critical decisions, many others can’t keep up because finding qualified individuals is a challenge.

According to the U.S. Bureau of Labor Statistics (BLS), “statistician” (a job category encompassing data analyst and data scientist) is one of the fastest-growing occupations in the United States. Training more people to step into data analysis roles supports this growth and helps more businesses and organizations reap the benefits of data insights. 

By attending Butler University’s MS in Data Analytics program, you will gain the knowledge and skills needed to analyze data and drive change within your organization. 


Butler University’s MS in Data Analytics program teaches the predictive analytics and effective visualization techniques essential for understanding complex datasets, as well as soft skills like critical reasoning and ethical decision-making. While you must have a bachelor’s degree to apply, it doesn’t have to be in data science, computer science, or any particular field.

Graduates exit Butler’s degree program with the qualities professionals need to succeed in this discipline, such as:

  • Analytical skills
  • Big Data analysis skills
  • Communication skills
  • Data visualization skills
  • Mathematics and statistics skills
  • Problem-solving skills
  • Programming skills
  • Project management skills

Earning an online Master of Science in Data Analytics at Butler requires the completion of 11 or 12 courses, depending upon your area of interest. You’ll begin with two foundational courses covering data management and analysis using R and Python scripting languages. From there, you’ll complete the following five core courses:

  • Advanced Analytics, Predictive Modeling, and Decision Making, which introduces advanced analytics and data mining models, including generalized linear regression models, mixture models, and time series models.
  • Data Engineering, Curation, and Analytics, which focuses primarily on techniques and tools for extracting data from various sources, preparing it for analysis, and applying those analyses.
  • Introduction to Data Mining, which covers current issues and methods in data mining and applications of data mining algorithms, including supervised and unsupervised machine learning techniques.
  • Text and Image Processing Techniques, which teaches how to use R and Python to develop and apply techniques to social media analytics and to process images and text to extract relevant information.
  • Visualization and Storytelling, which covers how best to report data to various audiences. 

You’ll then be able to choose from three different concentrations around which you will focus the remainder of your coursework: Bioinformatics (the analysis of biological data), Business Analytics (the application of data in business, e.g., marketing analysis or supply chain analytics), and Healthcare Analytics (the analysis of clinical and administrative data).

At Butler, you’ll learn from data analytics experts and make real-world connections while benefiting from the University’s flexible online model. Regardless of which pathway you choose, you can take just one seven-week course at a time. You’ll graduate knowing how to employ critical technologies such as data mining, machine learning, visualization, and predictive modeling. You’ll also be able to assess decisions strategically and appreciate the ethical implications of relying on data-driven algorithmic choices. And you’ll beef up your soft skills in storytelling as you learn to present visually compelling results to diverse audiences.


The answer to the question ‘What can I do with a master’s in data analytics?’ is more complex than ‘become a data analyst.’ As mentioned earlier in this article, the field of advanced data analysis is growing, which means opportunities for qualified and credentialed analysts abound. Additionally, there are several career paths you can follow once you have a graduate data analytics degree.

If you’re a generalist comfortable working in just about any department or field, you can become an analytics architect, analytics manager, or analytics specialist. Analysts with these titles handle a broad range of responsibilities related to data collection and organization.

If you prefer to capitalize on a specific skill set or your domain knowledge, you can specialize in roles, such as:

  • Big Data analyst: You’ll work with datasets too large to be cleaned, organized, stored, and analyzed in traditional ways.
  • Business intelligence analyst: You’ll use data to create finance and intelligence reports that inform decision-making.
  • Business intelligence architect: You’ll handle the optimization of data structures.
  • Information technology systems analyst: You’ll help align your organization’s IT assets with business goals.
  • Marketing analyst: You’ll look at market data to identify new ways to promote products and improve sales.
  • Transportation logistics specialist: You’ll use data to improve supply chain efficiency, stability, and cost.
  • Operations research analyst: You’ll tap into the power of data to advise decision makers on how to solve problems or meet goals.
  • Quantitative analyst: You’ll assess risk in financial markets with the help of statistical analysis.

Many of these job titles show up in multiple industries. Data analysts are especially critical in industries that need to predict market activity, detect and prevent fraud, and calculate and mitigate risk. This broad field has applications in just about every modern sector, including:

  • Entertainment, where it fuels content recommendations and performance measurement.
  • Education, where it tracks student progress and powers personalized learning technologies.
  • Manufacturing and retail, where it enables supply chain optimization, business planning, and demand forecasting.
  • Government, where it powers fraud detection and enhances environmental protection efforts.
  • Insurance, where it is useful for predicting policy-holder behavior and gauging risk.

Sectors as diverse as agriculture, energy, and real estate sales also employ data analysts. 


Earning an MS in Data Analytics can help you advance in your current career, pivot into a new role, and increase your earning potential. Most data analysts earn an average salary of about $80,000, though analysts with programming skills, artificial intelligence skills, or data science skills often earn much more. According to the latest Robert Half Salary Guide, experienced data analysts earn about $103,000. 

More importantly, data analysts also tend to enjoy their work, and many report being satisfied with their jobs. According to one PayScale survey, data analysts like the challenging nature of the role and the potential for advancement. When you become a data analyst, you can be sure your employers will value your specialized knowledge and skills, especially in today’s competitive marketplace because being able to leverage data insights can make a business. A lack of data talent can break it.


Demand for data analysts will continue to rise along with the rate of data generation and as organizations identify new data sources. Butler University’s Master of Science in Data Analytics program gives you the tools to help your organization make high-impact decisions that make the world a better place. The core curriculum covers ethical decision-making in addition to technical skills related to data mining, machine learning, visualization, and predictive modeling.

As more organizations rely on data to guide critical decision-making, data ethics becomes increasingly critical-to success and regulatory compliance. Butler’s expert faculty teaches MS in Data Analytics candidates how to use data to develop strategy while also considering the larger ethical implications of data use, data ownership, and data-driven decision-making.

Perhaps you are wondering if you really need a master’s degree to work in analytics. As new technologies blur the distinctions between analytics and data science, data analysts are reskilling and pursuing new credentials to keep up. One Burtch Works analysis found that 89 percent of data analysts with less than three years of experience have master’s degrees. While fewer than 10 percent of job postings for data analysts require that applicants have master’s degrees, according to research by IBM, you can be sure that number will go up. Now may be the best time to capitalize on the growing demand for data analysts with credentials that show they are capable of delivering value.

If you’re ready to start making a difference with data, learn about Butler’s admissions process, check out the MSDA program start dates, look at the MSDA tuition and financing, or apply online.