In today’s business world, data is easier than ever to collect and store. While the management of this big data is increasingly important to the decision makers in the organization, big data is ever more difficult to analyze.
Analytics professionals or data scientists are invaluable to an organization’s success. They have the unique combination of computational, analytical and communication skills necessary to discover data-supported solutions to important business questions, from an ever-increasing wealth of data.
- Understand why “big data” is so important in today’s business decisions
- Improve your data management skills
- Join the rapidly growing analytics field
- Big Data is #1 on Forbes.com’s list of Technical skills With Explosive Growth In Job Demand—Forbes.com lists big data as the number one in-demand technical skill, with an astonishing 3,977% increase in demand from 2011 to 2015. Read the full article…
- Big data training that pays off—CIO.com recently featured UD’s Certificate in Analytics in its list of big data programs that will give you an extra edge. Read the full article…
This program introduces students to the tools needed to analyze large datasets in order to make more informed business decisions. Students learn to gather and organize data for more effective analysis and how to communicate their analyses in a clear and concise manner. Topics include:
- Importing data into an analytics software package
- Performing exploratory graphical and data analysis
- Building analytics models using tools such as multiple regression and decision trees
- Finding the best model to explain correlation among variables
- Learning how to control and assess data variability to better meet customer requirements
To earn the Analytics Certificate, all of the following modules must be successfully completed with a grade of “C” or above.
- Analytics Basics
- Big Data Tools
- Process Control and Capability
- Individual Project
In this module, students will be introduced to the basics of analytics by learning key terms, concepts and knowledge areas and the use of SAS JMP analytics software. At the end of this module, students will be able to:
- Navigate JMP Software
- Input data from various spreadsheets and databases
- Perform graphical exploratory analysis
- Compare two or more groups
- Analyze paired data
- Use regression analysis to quantify the relationship between two variables
- Create and analyze a designed experiment
Big Data Tools
In this module, students will learn how to use big data tools to understand correlation among many different variables. At the end of this model, students will be able to analyze large datasets and build analytical models to predict future performance using the following multivariate tools:
- Neural Networks
- Partial Least Squares
- Principal Component Analysis
- Decision Trees
- Multiple Regression
- Cluster Analysis
- Discriminant Analysis
Process Control and Capability
In this module, students will learn how to evaluate if a process is stable and its ability to meet customer requirements. Students will also learn how to evaluate a measurement system’s performance and variability. At the end of this module students will be able to use the following tools:
- Process Control Charts
- Process Capability Analysis
- Measurement Systems Analysis
As a final requirement of the certificate, students will apply the concepts and techniques learned throughout the course to a case study project. The project will incorporate the use of a current data problem that the student would like to solve which will be approved by the instructor. Guidance in completing project milestones is done throughout the program.
Who should consider this program?
- Business, marketing, and operations managers
- Data analysts or professionals in any field who deal with large amounts of data
- Financial industry professionals
- Small business owners
While there are no formal requirements for admission to this program, please note the following recommendations:
- Statistics background—the course uses statistics throughout the curriculum. A basic understanding of statistics is recommended but not required.
- Some prior college coursework is recommended, as the modules are taught at the baccalaureate level and are fairly rigorous.
- Prior experience with data management is helpful.
- Study and class preparation—Most students have said that for every hour in class, they spent 1-2 hours outside of class studying and preparing for class.
- JMP® Pro statistical analysis software will be used in the classroom.
- A fully charged laptop (PC or Mac) is required to participate in this class.
- A copy of JMP® Pro statistical analysis software is included with this program, and the software is compatible with both Mac and PC.
"The ability to think conceptually about big data has been enormously helpful in transitioning to a new job that i was able to get during the course of the program." - Patrick Caruso
"This course has gone a long way in simplifying my workload and showing quick results to my internal customers." - Amogh Prabhu
"There is an explosion of data that can be found in every industry and government agency around the globe. The trick is to be able to take this data and turn it into information to drive better decisions." - Joe Messick