Academics are hampered by their ability to process and analyze increasingly large volumes of data in their research. Microsoft unveiled a cloud-based data analysis and processing framework called Project Daytona today in order to help address this problem.
Daytona is a tool kit that allows scientists to run a variety of analytics and machine-learning algorithms on Windows Azure. The idea behind the offering is to make the use of cloud-based analytics easy-to-use and also scalable, allowing users to use as many virtual machines as they want.
To date, the sites interface with software is limited to Excel, with a DataScope application that offers a library of data analytics and machine learning models, such as clustering, outlier detection, classification, and machine learning, along with information visualization. Users upload data in an Excel spreadsheet and then select an analysis model and processing parameters. One can easily see how such cloud infrastructure could easily apply to large geospatial processing projects if tied directly to GIS outputs and spatial analysis functions.
Read more about this framework and its capabilities in this Microsoft Research post.