InfoGuides: Big Data & Geovisualization: Storage & Visualization Tools

Tools for Storage and Computing

Argo Cluster Center: from Mason Office and Research (OCR) Computing Center. Mason faculty and staff, or a Ph.D student use only. Store and process your big data sets.
Globus: store and manage your big data (terabyte or petabyte). Choose Mason as an institution to proceed the site.
Spatiotemporal Hybrid Cloud Service Centers (stc): Big data analysis services hosted by Mason cloud service center (sponsored by NSF).
Apache Hadoop: an open source software framework for storing and processing data sets distributed across industry standard servers. See HDFS (Hadoop Distributed File System) and MapReduce to collect, aggregate, summarize all nodes. See the Hands-On Big Data Workshop presented at IASSIST 2015 Annual Conference (June 2, 2015).
Apache Hive: an open source software facilitates reading, writing, and managing large datasets residing in distributed storage using SQL.
Apache Spark: a fast engine for large-scale data processing.
Data APIs resources: a list of resources that provide an API to download big data in various formats (numeric, textual, images).
Tools for Collecting Twitter or other Social Media Data: Social Feed Manager (via GWU), CARTO, Getting Started with Twitter Data Collection with Python and Twitter APIs (via Mason Libraries), and NVivo Ncapture, etc.

ArcGIS Online: requires organizational account to do big spatial data visualization.
ArcGIS GeoEvent Server: capture real-time events based on query (Need to install ArcGIS Server on your machine).
ArcGIS GeoAnalytic Server: Cloud based server to visualize and analyze big data.
CARTO: a quasi open source for geospatial data mining and visualization.
Moving Pandas: explore big data visualization based on geopandas (Python based).
GIS Tools for Hadoop toolkit: open source toolkit for spatial analysis to big data and visualization by ESRI. See the tutorial to get started.
R for statistical computing: open source for statistical computing and data visualization with some mapping. See more resources at: Introduction to Spatial Analysis in R, R-Spatial (sp) (via CRAN-comprehensive R archive network ), R-Spatial.ly for maps and data visualization with R, and Book, "Applied Spatial Data Analysis in R" (Ebook is available via Mason Libraries).
Learn R (via Mason Libraries): infoguide on resources on learning R.
Tableau.com: data mining, statistical analysis and visualization. Also share information to public.