UNIVERSITY PARK, Pa. — Beginning Sept. 14, the Research Informatics and Publishing department at Penn State University Libraries will offer eight introductory and intermediate workshops on data analytics and visualization topics and tools commonly used for business analytics and big data analytics, such as Microsoft Power BI, Tableau, Azure, Amazon Web Services (AWS) and Google Cloud Platform (GCP).
In addition to a regular workshop session, GCP will offer lab and office hours for researchers.
Participants will have the opportunity to apply techniques to examples, discover resources necessary to get started with the tools, and learn about additional resources available at the University Libraries for continued self-learning.
Workshops are free and open to Penn State undergraduate and graduate students, postdoctoral scholars, faculty and staff. No previous experience is required for introductory-level workshops.
All workshops will be held virtually via Zoom. Advance registration is required; registration and additional information is provided at the link for each session below.
For additional information, contact Research Informatics and Publishing at repub@psu.edu.
Workshop Schedule
Introduction to Data Analytics and Visualization with Tableau — Sept. 14, 1–2:30 p.m.
This is a good workshop for those who have never used Tableau. Participants will learn the importance of data visualization and how to start working with Tableau, then follow examples on how to connect to a dataset and create and share visualizations. You’ll discover differences between Tableau Public and Tableau Desktop and learn about some of the training resources available. No prior experience is required.
Introduction to Data Analytics and Visualization with Power BI — Sept. 21, 1–2:30 p.m.
This workshop will provide an overview of Power BI as one of the most popular data analytics and visualization tools on the market. You will learn how to access the tool, connect to data and perform basic data transformations, build common visualizations, and share your reports online. No prior experience is required.
Data Modeling with Power BI — Sept. 28, 1–2:30 p.m.
In this session you will gain an understanding of what data modeling is and why it is important. You will have the chance to build an efficient data model in Power BI by following an example. It is recommended to attend Introduction to Data Analytics and Visualization with Power BI before taking this workshop.
Analyzing Survey Data with Power BI — Oct. 5, 1–2:30 p.m.
This workshop is ideal for anyone who would like to learn about analyzing survey data with Power BI. We will connect to a raw data file, create visualizations and build a report that’s ready to share with others. You will learn about the challenges you might experience when trying to connect to data in Power BI in its original form generated by MS Forms, as well as best practices for designing visualizations to present survey data. It is recommended to attend Introduction to Data Analytics and Visualization with Power BI before taking this workshop.
Introduction to Azure OpenAI Service and ChatGPT — Oct. 12, 1–2:30 p.m.
Artificial intelligence (AI) is advancing quickly and grabbing headlines every day. Experiences based on large language models, like ChatGPT, have taken the world by storm. In this session, we’ll discuss generative AI and the Azure OpenAI Service offered by Microsoft as part of its partnership with OpenAI. We’ll learn how Azure OpenAI Service can be used to build intelligent applications and how its powerful large language models are changing the way we work. This session is ideal for anyone interested in learning more about Azure OpenAI Service and its potential applications.
Workshop: Introduction to Big Data Analytics in the Cloud: Google Cloud Platform — Oct. 25, 1–2:30 p.m.
Experts from the Google Cloud team will share how Google’s artificial intelligence (AI) tools can help higher education institutions increase engagement with their students, improve institutional operations, and optimize research workloads. They will share relevant trends in education and research while highlighting compelling customer stories. Bring your whole team and start the discussion of how you can use Google Cloud AI to build innovative solutions to your work challenges. In this session you will learn how Google tools can be applied to high-performance computing, how to use AI/ML to enhance decision making and increase operational efficiency, how to leverage AI/ML within research and use large language models in nonscience applications for research.
Lab: Introduction to Big Data Analytics in the Cloud: Google Cloud Platform — Oct. 26, 1–2:30 p.m.
This session will provide hands-on experiences with the Google Cloud team, diving deeper into the concepts presented in the workshop session.
Introduction to Big Data Analytics and AI/ML Services: Amazon Web Services — Nov. 2, 1–2:30 p.m.
This session will look at the unique ability of cloud computing to process, analyze and draw insights from the massive amount of data generated by today’s modern, distributed systems. The session will cover use cases for data lakes, querying them using Amazon Athena, as well as an overview of core artificial intelligence and machine learning services like Amazon Rekognition, Amazon Polly, Amazon Lex, Amazon Comprehend, and Amazon SageMaker.