In today’s business and financial worlds, data is a necessary tool behind nearly every decision, big or small, no matter the industry.
Being a leader in business now and in the future requires solid data analytics skills and experience with various data analytics tools to evaluate and interpret that data to execute numerous business functions, from planning to decision-making.
Gaining sought-after data analytics skills and credentials — including a data analytics degree — can help you position yourself to meet a wide range of societal and business needs across myriad careers in business and beyond.
But what are data analytics skills, and how could a data analytics degree help you develop them? Read on for more information about data analytics, data analytics skills and tools, earning a graduate data analytics degree and more.
Data analytics provides a framework to analyze data and translate it into actionable insights that address challenges and help businesses and organizations navigate issues in virtually all industries.
Analyzing data to create actionable solutions begins with gathering and organizing information, gaining a clear understanding of what happened in the past and drawing on those findings to formulate plans for the future. Data analytics falls into four main categories, which essentially are based on the issue it seeks to solve.
The four types include:
Helps discover and describe what happened in the past through several data analytics skills and tools, including data mining and aggregation.
Partially rooted in probability and drawing on myriad data analytics skills and techniques, this helps professionals determine why an event happened.
Utilizing probability and various data analytics skills and analysis techniques (including predictive modeling), this helps professionals anticipate potential outcomes.
Helps organizations and businesses determine the next steps for any given circumstance by drawing on many analysis techniques and data analytics tools, such as simulation analysis, and may draw on artificial intelligence.
Successful business data scientists and data analysts and other professionals analyzing and working with data must employ a wide range of data analytics skills on the job, from analytical know-how to communication.
Specific roles and industries may require additional skill sets, but experts generally agree that common and important data analytics skills may include:
Professionals in any role who are dealing with data analytics must also be able to properly present and convey the results of their work to audiences of all knowledge and skill levels.
From writing or improving code and algorithms to employing data visualization tools, professionals working with data must have well-developed computer skills, including a solid background in computer programming and language, such as Structured Query Language (SQL), Python, R, C and others.
Professionals who work with and analyze data must be critical thinkers and problem-solvers in order to understand the issues at hand and devise frameworks to help provide solutions.
Nearly all functions related to working with data analytics require some form of math, from statistics to probability. Therefore, math skills — especially those related to applied statistics — will help professionals carry out this work.
To work in data analytics, professionals in all roles must be skilled researchers who can also properly examine and interpret their findings.
From data mining to working with predictive modeling, professionals gathering and interpreting data need experience working with a variety of data analytics tools to properly carry out their tasks and address and communicate their findings.
From hospitality and finance to social sciences, media and public relations, there are myriad undergraduate and graduate courses for data analytics designed to specifically address data analysis across these industries and others.
Michigan State University’s M.S. in Business Data Science and Analytics program offers graduate courses that explore applied statistics, data mining, data analytics tools and more, all taught by leading MSU instructors.
If you’re exploring a graduate-level data analytics degree, some of MSU’s relevant courses include:
Learn to apply statistical concepts including random variables, analysis of variance and others while developing an understanding of when to use which.
Examine emerging issues in big data, such as collection and querying, mining and association analytics, and more.
Learn about analytics’ role in shaping competitive strategy and improving the design and implementation of business processes.
Explore techniques and algorithms for knowledge discovery in databases.
Delve into concepts and their applications, supervised learning (such as penalized regression, classification and survival analysis), deep neural networks for classification, advanced topics in machine learning (such as generative models and meta learning) and more.
Now that you’re more familiar with business data analytics skills and tools, explore the next steps toward your future in virtually any industry with a graduate data analytics degree from MSU — specifically, our Master’s in Business Data Science and Analytics.
This program, through multiple experiential learning opportunities, will provide you with the knowledge, practice and data analytics skills that working in this field requires. Each semester, this data analytics degree program offers graduate students the opportunity to work on data sets arranged with corporate and faculty support.
In addition to the aforementioned courses, when you earn a business data analytics degree at MSU, you’ll also study business strategy, project management, marketing technologies and communications, rounding out your skill set to help you build or advance your career, no matter your aspirations.