lets scientists run a variety of analytics and machine-learning algorithms on Windows Azure; frees scientists coding by giving them the ability to analyze their largest data collections.
CNET, by Jay Greene, July 18, 2011
Microsoft unveiled new technology today designed to give academics better tools to harness the vast quantities of data available to them.
"We're living in a data deluge right now," said Tony Hey, corporate vice president of Microsoft Research Connections.
Scientists generate massive data in their work in areas such as environmental science, particle physics, astronomy, and other disciplines. Analyzing that information becomes ever more cumbersome.
So Microsoft released Daytona,
a tool kit that lets scientists run a wide variety of analytics and machine-learning algorithms on Windows Azure. The technology is intended to free up those scientists from having to code their own software tools, giving them the ability to analyze their largest data collections and focus on their work.
Daytona: Iterative MapReduce on Windows Azure,
Project Daytona was developed as part of the eXtreme Computing Group's Cloud Research Engagement Initiative, making its debut at the Microsoft Research Faculty Summit. One of the most common requests we have received from the community of researchers in our program is for a data analysis and processing framework. Increasingly, researchers in a wide range of domains-such as healthcare, education, and environmental science-have large and growing data collections and they need simple tools to help them find signals in their data and uncover insights. We are making the Project Daytona MapReduce Runtime for Windows Azure download freely available, along with sample codes and instructional materials that researchers can use to set up their own large-scale, cloud data-analysis service on Windows Azure. In addition, we will continue to improve and enhance Project Daytona (periodically making new versions available) and support our community of users.