Skills, Concepts, or Opportunities Gained with a Master’s Degree in Data Analytics
A typical master’s in data analytics curriculum consists of courses that can give students in-depth knowledge and skills in several aspects of data analytics. Many of these data analytics courses will cover the following skills, concepts, or opportunities:
- Looking for trends, making decisions, and identifying opportunities. More than ever, businesses and organizations are using large amounts of data to make decisions, increase revenue, and find efficiencies; however, all of that data is meaningless without proper analysis. It is critical that students in this field learn how to look for patterns and trends within the data that can signal opportunities or threats and drive decision-making.
- Combining operational data with analytical tools. Operational data, which includes data on competitors, suppliers, and finances, can be turned into meaningful information with the right analytical tools. This analysis can, in turn, help improve existing operations.
- Presenting complex and competitive information. The amount of data at the fingertips of individuals, organizations, and businesses is staggering. As such, it’s critically important for data analytics professionals to be able to present this information in such a way that other stakeholders — company leadership, for example — can understand it. It’s not enough to just analyze the data; people working in data analytics must also be able to effectively communicate their findings.
Common Courses for MS in Data Analytics Students
These are some of the common courses offered for a data analytics degree. Though actual course titles may vary depending on the university, many data analytics programs offer courses that touch on the following concepts:
Data Analytics. The proper use of data, quantitative analysis, and modeling is driving an increasing number of business decisions. All data analytics students need to be comfortable with analyzing different types of data, using different programming languages, and drawing actionable insights from what they discover.
Database Principles. Much of the data that needs to be analyzed is housed in databases. Becoming familiar with database tools and architecture and relevant security issues is essential for data analytics professionals.
Data Visualization. Looking for and finding meaningful insights in large amounts of data is only half of the job — aspiring data analytics professionals must also be able to visualize the data in a meaningful way in order to inform business decision-making. Common forms of data visualization include charts, graphs, and maps.
Forecasting and Predictive Modeling. The field of predictive analytics is growing quickly within data analytics. Businesses often use forecasting and predictive modeling in order to best predict what may happen in the future.