Location
BELC, South Wing, S269
Data Visualization Lab
In Bryant University’s Data Visualization Lab, students gain practical experience with the technology, tools, and applications used by data science and analytics professionals, such as 2D, 3D, and graph visualization, as well as virtual reality (VR) capabilities. This hands-on learning challenges students to transform complex data into comprehensible information that can then inform strategic decision-making.
The lab supports technology-driven courses, especially those focused on data visualization, and fosters experiential learning for the entire Bryant community. Open to students from all programs, the lab serves as a collaborative space where students can explore its many resources.
Together, the Data Visualization Lab, Data Science Lab, and Artificial Intelligence Lab form the Data Science hub within the Business Entrepreneurship Leadership Center. Through the space’s active-learning classrooms, students and faculty can explore the transformative potential of data science and AI in business.
Highlights
Students benefit from cutting-edge technology and equipment, including:
- Two large display monitors with touchscreen and annotation capabilities
- 13 graphics processing unit (GPU)-based computers with specialized software
- Podium workstation with camera, annotation tool, and touchscreen monitors
- Small group workstations with VR headsets, cameras, and touchscreen monitors
- High-performance servers
- Moveable furniture and ergonomic, adjustable desks
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“The Data Visualization Lab fosters collaboration and critical thinking by encouraging students to examine data and explore effective communication techniques. Providing students with these opportunities builds their confidence and ability to not only understand data and technology but also harness the power of visualization.”
Geri Louise Dimas
Associate Professor
13
GPU-based computers with specialized software
2
large touchscreen monitors
Selected Courses Offered in the Lab
ISA 310: Data Visualization
This course examines the art and science of data visualization, exploring the way that shape, size, color, orientation, and motion influence how information is comprehended. Students will study a wide range of techniques for creating effective visualizations using products like Excel, Tableau, Gephi, and Python.
This course examines the art and science of data visualization, exploring the way that shape, size, color, orientation, and motion influence how information is comprehended. Students will study a wide range of techniques for creating effective visualizations using products like Excel, Tableau, Gephi, and Python.
ISA 460: Big Data Analytics
This course brings together key big data tools to show how to efficiently manage data with three main characteristics: volume, velocity, and variety. Topics include the Hadoop platforms, Teradata Aster, social media analytics, link analysis, and stream analytics.
This course brings together key big data tools to show how to efficiently manage data with three main characteristics: volume, velocity, and variety. Topics include the Hadoop platforms, Teradata Aster, social media analytics, link analysis, and stream analytics.
ISA 520: Data Visualization and Communication
This course teaches how to visually explore data and how to criticize, design, and implement data visualizations. Students will learn multiple popular data visualization tools such as Power BI, Tableau, and Python to implement data visualization projects throughout the course.
This course teaches how to visually explore data and how to criticize, design, and implement data visualizations. Students will learn multiple popular data visualization tools such as Power BI, Tableau, and Python to implement data visualization projects throughout the course.
AA 304: Managing Information for Applied Analytics
This course is about the management of information, how it is acquired, stored, and deployed effectively, and how it may be analyzed for applications in a wide variety of domains such as literary and historical text analysis, social media, bioinformatics, and business decision-making.
This course is about the management of information, how it is acquired, stored, and deployed effectively, and how it may be analyzed for applications in a wide variety of domains such as literary and historical text analysis, social media, bioinformatics, and business decision-making.
AA 640: Data Visualization and Text Mining
This course exposes students to text mining techniques using unstructured data. Students will understand the challenges of working with unstructured data such as text and images. Students will also learn the techniques to implement efficient and effective data visualizations.
This course exposes students to text mining techniques using unstructured data. Students will understand the challenges of working with unstructured data such as text and images. Students will also learn the techniques to implement efficient and effective data visualizations.