Data Visualization and
Predictive Analytics Workshop

Pricing

Scholarships

Hotel

Schedule

Workshop Descriptions

Course Description

Colleges and universities are increasingly reliant on data to make decisions and solve problems. As a result, business officers need to know how to search for and utilize key metrics that identify and solve problems.

This technical workshop walks through the data life cycle from gathering data, organizing it in a meaningful way, exploring the data for insights, using metrics to solve problems using data visualization, and presenting data to top level administrators.

Time and guidance will be provided to experiment with the techniques covered in the course. We will use Tableau, an industry-leading software for data visualization. No prior knowledge is required. 

Learning Objectives

• Gain familiarity with general principles of selecting metrics and visualizing data
• Understand principles for using data to brief senior leadership
• Become acquainted with methods for exploring a dataset
• Practice creating visualizations and dashboards in Tableau
• Learn about new technologies for data visualization

Presenter

Course Description

Predictive analytics is a phrase that litters the news, but one with which many business officers have little experience. We often hear about predictive analytics and data mining technologies being applied to enrollment and retention problems, but it may not be immediately obvious how the business and finance parts of an institution can use these technologies. Further, the terminology can seem arcane, with techniques drawn from statistics, computer science, and a variety of other technical areas. This workshop will teach participants how to use data mining and predictive analytics to improve the efficiency of their institution.

The session will cover the full life cycle of a project, from idea to implementation and assessment. No prior knowledge of data mining will be assumed, although a basic understanding of statistics is helpful. We will use RapidMiner, an industry-leading data mining tool that requires no programming skills.

Learning Objectives

• Understand the terminology and tools involved in predictive analytics, data mining, and other advanced analytic techniques
• Learn a repeatable process for advanced analytics that can be applied to a variety of business problems
• Gain experience using an open source, menu driven tool to perform and interpret an analysis
• Practice assessing the results of an analysis to determine next steps

Presenters

Mark Naufel received a bachelor’s degree in finance and master’s degrees in both business analytics and systems engineering from Arizona State University. As an undergraduate, he served as student body president and was later appointed by the Governor of Arizona to serve a two-year term on the Arizona Board of Regents as the Student Regent. Currently he is pursuing a PhD in human systems engineering at ASU. Mark is the Executive Director of Strategic Projects at ASU’s Knowledge Enterprise and leads an interdisciplinary lab of exceptional students called The Luminosity Lab. Luminosity is an applied research and development lab that aims to positively impact society through the use of emerging technologies. Previously, Naufel drove strategy and data initiatives for companies both locally and in Silicon Valley - working at companies such as Cisco Systems, The Wolff Company and the Arizona Chamber of Commerce. He also served as the political director for one of Arizona’s political parties, leading political and data strategy for the 2014 statewide races, and was nominated by Arizona Capitol Times as one of Arizona’s rising political stars.