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Data Analytics & Visualization

Introduction to the data analytics and visualization software programs and consultation service available at the Advanced Analytics and Visualization Digital Lab at Libraries' Research Informatics and Publishing.


The Department of Research Informatics and Publishing enhances the technology-driven teaching and research capacity of the Penn State community. We partner with students, faculty, and staff to consult, provide training, and support projects in the areas of research data management, digital humanities, mapping, statistical analysis, data analytics and visualization, and open publishing. Our services are based on the tenets of openness, innovation and technology, collaboration, and supporting the entire research workflow.

  • The general workflow for data analytics and visualization is to gather data sources; consolidate data, pre-process data including filtering, aggregation, transformation, and other data tasks; model data, including creating models, estimating and validating models; analyze results, including description, prediction, prescriptions, and impact evaluation; visualize the result with user interaction.
  • What are the types of Data Analytics applications?
    • Business Intelligence (BI) and reporting: it provides business executives and other corporate workers with actionable information about key performance indicators, business operations, customers, and more. – SearchDataManagement
    • Advanced Data Analytics: it includes data mining, which involves sorting through large data sets to identify trends, patterns, and relationships; predictive analytics, which seeks to predict customer behavior, equipment failures, and other future events; and machine learning, and artificial intelligence technique that uses automated algorithms to churn through data sets more quickly than data scientists can do via conventional analytical modeling. Big data analytics applies data mining, predictive analytics, and machine learning tools to sets of big data that often contain unstructured and semi-structured data. Text mining provides a means of analyzing documents, emails, and other text-based content.  – SearchDataManagement

Consultation service and learning resources

Use the following links to download the software you need for your data and analytics projects. We recommend using the official documentations as learning resources, they are very well designed and allow you to learn in a systematic way. If you would like to discuss your research projects with us, please contact us for a one-to-one consultation by appointment. In addition, we launched an Advanced Analytics and Visualization Digital Lab in Jan, 2019 to provide computers with specialized software programs, such as Power BI, Tableau, R, Python, SAS, SPSS, STATA, ArcGIS. Currently, the computers and software are available to faculty and students via 

Business Analytics

Big Data Analytics & Machine Learning

Besides the documentation from the official websites, we recommend other great learning resources, such as,, and Penn State Institute for Computational and Data Sciences (ICDS) that offer workshops, software programs, and High-Performance Computing (HPC) platforms, or join PSU Data Analytics degree programs. Penn State University Libraries, Cloud Services team and ICDS provide research consultations for using different data and analytics tools.

Spring 2021 workshops

Penn State University Libraries will continue to offer Data Analytics and Visualization sessions this semester via Zoom. It highlights part of the Research Data Services offered by the Libraries’ Research Informatics and Publishing department

These sessions are aimed at introducing the resources and expertise available at the University Libraries in Data Analytics and Visualization and offering an opportunity for hands-on experience using the available software tools at the university libraries.

The sessions are free and open to all Penn State students, staff, and faculty. Advanced registration is recommended.

Data Analytics & Visualization Fall 2020 sessions

Title Description Date Time Meeting Info
Introduction to Data Analytics and Visualization with Power BI and Tableau Learn basic tools in Power BI and Tableau for data analytics and visualization with demos Thursday, Oct.15, 2020 2:00 - 3:30 pm Webinar ID: 933 1530 1665
Passcode: 799427
Data Modeling and Data Transformation with Power BI and Tableau How to clean, transform, and create relations among data tables? sample data will be used for demos Thursday, Oct. 22, 2020 2:00 - 3:30 pm Webinar ID: 960 9096 2011
Passcode: 210820
Introduction to Big Data Analytics with Power BI and Tableau Learn basic tools in Power BI and Tableau for big data analytics (R or Python) with demos Thursday, Nov.05, 2020 2:00 - 3:30 pm Webinar ID: 937 2542 2732
Passcode: 544029
Big Data Analytics with MS Azure or Google Cloud Platform Learn the big data analytics tools in Azure and Google Platform with demos Thursday, Nov. 12, 2020 2:00 - 3:30 pm Webinar ID: 928 2159 7960
Passcode: 136647


The general scope and purpose for these sessions are to overview the subject of data analytics, also to explore some commonly used software tools by demonstrating data analysis and visualization process based on some public sample datasets. Information about online resources, available university libraries’ resources (computers and software programs), and one-on-one consultation service from Research Data Services at Research Informatics and Publishing will be provided.

Contact: Xuying Xin, Data Analyst (Certified Tableau Desktop Specialist and MS Power BI),

Spring 2020 workshops:

Data Visualization with Tableau

Thursday, Jan. 30, 2020, 2:00-3:30 p.m., W312A Pattee Library.

Introduction to Database - MS Access & Excel

Thursday, Feb. 27, 2020, 2:00-3:30p.m., W312A Pattee Library

Business Analytics with MS SQL Server & Business Intelligence (BI)/SSIS, SSAS, SSRS

Thursday, Mar. 26, 2020, 2:00-3:30p.m., W312A Pattee Library

Data Visualization with Power BI Desktop

Thursday, Apr. 23, 2020, 2:00-3:30p.m., W312A Pattee Library