So a UAS and a cloud walk into a juice bar...
The UAS says "I've got so much data I don't know where to store it all...Hey, you're a cloud, can you help me out?" And the cloud says "I'd love to but I'm just a cloud, what you need is a server".
But seriously folks... the growing ability for servers to store, analyze, and disseminate large amounts of different types of data will allow businesses looking to capitalize on data collected from UAS to effectively manage their data and provide fast, reliable solutions to their customers. Consumers of geospatial data are often not interested in performing manual analysis on the data in order to derive the information they need. They want accurate solutions delivered to them via simple-to-use interfaces that provide the answers they want without bogging them down with unnecessary steps or irrelevant information. This is where the analytics come in.
So a UAS walks into a juice bar and says to the cloud behind the counter...
"I've got forty gigabytes of LiDAR data, eighteen multispectral and six hyperspectral images taken over the period of twenty-four months, and some historical rainfall and other weather related data over a specific set of agricultural fields. Can you help me understand how to better manage these fields to reduce my overall operating costs and increase my overall yield?" And the cloud says "What you need are some enterprise analytics, I'm just a cloud working at a juice bar".
But seriously folks... without the ability to host and disseminate different data types, as well as reliable algorithms to perform analysis on data and fuse the derived information into understandable solutions, much of the imagery and other geospatial assets captured by UAS will simply collect dust in a database and never see the light of day.