Data Analytics Engineering

Overview

The Department of Mechanical and Industrial Engineering offers the Master of Science in Data Analytics Engineering in order to meet the current and projected demand for a workforce trained in analytics. While the core courses for this program are offered by the College of Engineering, elective courses can be chosen from diverse disciplines spread across various colleges at Northeastern. 

The program from Northeastern University is designed to enable graduating students to address the growing need for professionals who are trained in advanced data analytics and can transform large streams of data into understandable and actionable information for the purpose of making decisions. The key sectors that require analytics professionals include healthcare, smart manufacturing, supply chain and logistics, national security, defense, banking, finance, marketing, and human resources.

This degree program seeks to prepare students for a comprehensive list of tasks including collecting, storing, processing and analyzing data, reporting statistics and patterns, drawing conclusions and insights, and making actionable recommendations.

Program Objectives

The MS in Data Analytics Engineering is designed to help students acquire knowledge and skills to:

• Discover opportunities to improve systems, processes, and enterprises through data analytics
• Apply optimization, statistical, and machine-learning methods to solve complex problems involving large data from multiple sources
• Collect and store data from a variety of sources, including Internet of Things (IoT), an integrated network of devices and sensors, customer touch points, processes, social media, and people
• Work with technology teams to design and build large and complex SQL databases

• Use tools and methods for data mining, big-data algorithms, and data visualization to generate reports for analysis and decision-making

• Create integrated views of data collected from multiple sources of an enterprise

• Understand and explain results of data analytics to decision makers

• Design and develop analytics projects