Below is a table with a list of commonly used data analysis tools and corresponding tutorials.
| Tools | Description | Tutorials |
| SPSS | [Free to SJSU student, faculty, staff] Used for statistical analysis of quantitative data. The graphical user interface makes statistics analysis easier, including most complex models. | SPSS Tutorial |
| SAS | [Free to SJSU faculty] A powerful statistical-analysis and data-management system for complex data sets. It is especially strong in analysis of variance (ANOVA), the general linear model, and their extensions. | SAS Tutorial |
| QGIS | [Free] It is open source GIS software, available for both Windows and Mac OS. This software has a powerful and useful features. | QGIS Tutorial |
| R | [Free] R is an open-source programming language and command-based application. This language is a powerful visualization and analysis tool for data. R is primarily used for text mining. | R Tutorial |
| Stata | [Not Free] A command-based statistical package that offers a lot flexibility for data analysis. The program language keeps a simple structure, so is easy to learn, allowing users to focus on the statistical modeling. | Stata Tutorial |
| NVivo | [Not Free] A qualitative data analysis package. It helps researchers organize and analyze complex non-numerical or unstructured data, both text and multimedia. The software allows users to classify, sort, and arrange thousands of pieces of information. It also accommodates a wide range of research methods. It supports documents in many languages. | NVivo Tutorial |
| Dedoose | [Not Free] A web-based qualitative analysis tool for data including text, audio, images, or video; and quantitative data such as spreadsheets, surveys, test scores, ratings or demographics. | Dedoose Tutorial |
This link below will take you to a page where you can learn about the types of data visualization, design considerations, tools, and infograhics.