Introduction

• What is Data Analytics? It is the science of examining raw data with the purpose of drawing conclusions about that information. - SearchDataManagement
• What is Data Visualization? Data visualization refers to the techniques used to communicate data or information by encoding it as visual objects (e.g., points, lines or bars) contained in graphics. - Wiki
• What are the differences Data Visualization vs. Data Analytics? Data visualization represents data in a visual context by making explicit trends and patterns inherent in the data; Data analytics go a step deeper, identifying or discovering the trends and patterns inherent in the data with tools and algorithms. - Fingent
• How are Data Analytics and Data Visualization integrated into one workflow?- Alam et al. 2017
• 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, an 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

Available resources and consultation service

Use the following links to download the software you need and we recommend the official documentation as learning resources. If you would like to discuss your research projects, the Advanced Analytics and Visualization Digital Lab from the Research Informatics and Publishing provides one-on-one consultation service to the research community by appointments. The Digital Lab offers computers with the following software programs.

Business Analytics

• Download links (MS applications are free to PSU users as part of Office 365 group license, log in for free download)
  • MS SQL SERVER Express (PC): https://www.microsoft.com/en-us/sql-server/sql-server-downloads
  • MS POWER BI (PC or online): https://www.microsoft.com/en-us/download/details.aspx?id=58494
  • MS Access (PC): https://www.microsoft.com/en-us/microsoft-365/buy/compare-all-microsoft-365-products?tab=1&rtc=1
  • Tableau Public (Mac or PC): https://public.tableau.com/en-us/s/download;
  • Tableau offers free one-year Tableau Desktop license for teachers and students
    • Tableau for students: https://www.tableau.com/academic/students
    • Tableau for teaching: https://www.tableau.com/academic/teaching
• Learning resources
  • MS Power BI: https://docs.microsoft.com/en-us/power-bi/guided-learning/; https://catalog.libraries.psu.edu/catalog/29282447
  • Tableau Public: https://public.tableau.com/en-us/s/resources; https://www.tableau.com/learn/training/20194
  • MS Access: https://support.microsoft.com/en-us/office/access-video-training-a5ffb1ef-4cc4-4d79-a862-e2dda6ef38e6
  • MS SQL Server: https://docs.microsoft.com/en-us/sql/sql-server/tutorials-for-sql-server-2016?view=sql-server-ver15
  • MS Excel: https://support.microsoft.com/en-us/office/excel-for-windows-training-9bc05390-e94c-46af-a5b3-d7c22f6990bb

Big Data Analytics & Machine Learning

• Access the online platforms
  • MS Azure (Get started with 12 months of free services): https://azure.microsoft.com/en-us/free/
  • Google Cloud Platform/GCP (Start running workloads on GCP for free): https://cloud.google.com/free/
• Learning Resources
  • MS Azure: https://docs.microsoft.com/en-us/learn/paths/azure-fundamentals/
  • Google Cloud Platform (GCP): https://cloud.google.com/bigquery/docs/tutorials

Besides the documentation from the official websites, we recommend other great learning resources, such as https://lynda.psu.edu/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. 

Upcoming 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

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), xzx1@psu.edu

Past 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