Overview: 

Introduction to Engineering Analytics is our newest class and offers the latest on Big Data and data visualization. In this course, engineers, managers and anyone who wants to understand how Big Data will impact their operations will be introduced to the fundamentals of engineering analytics, that is, the process of leveraging data into actionable insights. These strategies will be applicable to a wide range of applications including customer segmentation for better resource utilization, improved performance tracking for diagnosis and maintenance, classification strategies for improved inventory management, better use of sales data for increased revenues and customer satisfaction, and better forecasts.

Basic methods will be introduced in the areas of descriptive and predictive analytics and Big Data. Participants will gain hands-on experience through the use of case studies and example problem demonstrations. Throughout this introductory program, Microsoft-based tools such as Excel will be used when appropriate. Other analytics software tools, in particular those that are in the public domain, will be discussed.

Participants should bring a laptop running Windows with Excel installed.

What You Will Learn:

• Apply techniques for data visualization
• Describe the importance of segmentation and classification strategies
• Use basic tools of descriptive and predictive analytics 
• Interpret the impact of Big Data on decision making
• Describe the underlying technology in Big Data
• State the strategic implications of analytics

Course Content

• Introduction to engineering analytics 
• Data visualization strategies
• User interaction
• Business impact
• Descriptive analytics: data models
• Data properties
• Databases
• Design issues
• Regression techniques 
• Clustering
• Segmentation
• Case study illustration
• Descriptive analytics: classification strategies
• Measures of accuracy
• Predictive analytics: introduction principal component analysis
• Principal component analysis for prediction
• Predictive analytics: forecasting 
• Data models
• Big data: enterprise modeling
• Optimization techniques