Unless you are a brand new startup, you probably have legacy systems that your new applications need to integrate with. Of course, it doesn't have to be legacy data. It could be new IoT, analytics or other digital data you will be generating. Unless you plan to host all of this data on the public cloud, you probably need to consider a private cloud. Sure, you could purchase a direct link to a public cloud and host your apps there, but all this data transfer is likely to get very expensive if there is a lot of data going back and forth.
From Big Data projects like Strayer University's student support system to AI projects like Carnegie Mellon's socially aware robot, researchers are discovering that cloud technology can help make academic research cheaper, faster, easier, and more secure. Whether you're just starting out with a new idea, or validating your work before sharing it with the public, we want to help you advance your new discoveries. Academic researchers in qualified regions are encouraged to apply. Like the Google Cloud Platform Education Grants to support computer science courses and the partnership to support National Science Foundation (NSF) grants in BIGDATA, our GCP research credits program supports faculty who want to take advantage of GCP's data storage, analytics, and machine-learning capabilities. Andrew V. Sutherland, a computational number theorist and Principal Research Scientist at the Massachusetts Institute of Technology, is one of a growing number of academic researchers who have already made the transition and benefited from GCP.