Master of Science in Applied Data Analytics
With the growth of the digital age businesses and organizations have had access to unprecedented amounts of data. In order to turn this data into a competitive advantage businesses must develop effective methods to analyze and interpret vast amounts of information. Part business management and part data science, Applied Data Analytics is the key to developing methods that unlock the predictive potential of data.
Applied Data Analytics plays an integral role in determining an organization’s overall strategic direction, and demand for this crucial set of skills is growing globally. The McKinsey Global Institute expects that demand for businesspeople with deep analytical skills could outstrip current projections of supply by 50% to 60%. Graduated students can expect to play a greater role in decision making and strategy setting for their current or future organizations, adding significant value: studies show that businesses that understand how to interpret data outperform competitors by up to 20%. New England College’s Master of Science in Applied Data Analytics provides students with frameworks for critically looking at data, interpreting and visualizing data, and applying that knowledge in real-world applications that will shape how 21st century business challenges are addressed.
Who Should Enroll
The Master of Science in Applied Data Analytics is useful for anyone with a bachelor’s degree, with or without experience, wishing to prepare for the emerging global opportunities in data analytics and business statistics.
- 7 start times throughout the year
- 36 credit program
- Learn how to effectively leverage data for strategic decision making
- Learn methods to evaluate data from acquisition, cleansing, warehousing and final analyses
- Understand ways to leverage internet presence to harvest big data
- Understand methodologies and tools for collecting data and designing databases
- Proficiency in interpreting collected data using a variety of statistical tools
- Execute real-time analytical methods on living datasets to quickly respond to a customer’s wants and needs