InfoGuides: Data Analytics Engineering: Find Software & Tools

Software & Tools for Working with and Visualizing Data

The following software and tools will help you work with your data and create interesting visualizations. Clicking on the blue name for each tool will take to you resources to help you learn more about the tool and how to use it. For additional tools for working with data, check out the following research guides: Text & Data Mining, Text Analysis Tools and Data Visualization.

R
R is a programming language used by statisticians and DAEN students. Users can download packages to do data cleaning/manipulation, text/data mining, data visualization, geospatial mapping and statistical analysis.
Python
Python is a general purpose programming language that provides users with Python packages they can use for data analysis. It is recommended that you download the Anaconda platform (with over 1,000 pre-installed packages) if you want to do data analysis. Python is very useful when working with data that must be scraped from the web (Beautiful Soup package).
Tableau
Tableau is an interactive tool for creating data visualizations. The drag-and-drop interface allows you to build geospatial maps and different types of graphs from data store in CSV or Excel format. You can paste charts together to create an interactive dashboard.
Microsoft Power BI
Microsoft Power BI is a suite of business analytics tools similar in functionality to Tableau. This tool's cloud-based infrastructure provides an easy way to upload, save and share data.
MicroStrategy
MicroStrategy is a data visualization and predictive analytics tool tht can be used to create dashboards. Unlike Tableau and Microsoft Power BI, MicroStrategy works with "big data" and can pull data from a variety of sources including Apache and Hadoop distributions.
Weka
Weka is a tool used to implement machine learning algorithms for data mining. The algorithms can either be applied directly from the GUI or from Java code. It can be used for data pre-processing, classification, regression, clustering and visualization.