it's a vague question so here's a vague answer :)
Hadoop on its own is a tool to run map-reduce jobs in a cluster, it's highly optimized for performance and a good deal of this optimization is done by distributing the data in a way that makes it easy to consume without incurring on I/O penalties.
for this you should read about HDFS and the internals that explain how is this done, in a nutshell what happens is that the input data is clumped together in nodes to run the processes locally and read sequentially (this is a property/limitation of HDFS).
this way you input your "BigData" and it gets split and processed in the most efficient way inside the cluster.
now that' all there is to Hadoop itself, there's tools that work on top of it that allow you to perform high-level abstractions on the data (map-reduce is among the simplest procedures).
those include:
Specifics for .Net
For Hadoop on Azure (.Net) , there's an introduction on msdn here with more info here. Related to building Hadoop applications through their platform.
It's only CTP for now, but off course this will change.
Here's another good blogpost about Hadoop and MapReduce with code
Additionally, there's also a company that frequently gives information about Hadoop: Cloudera, you should check there frequently for more information.
For more information, check the cloudera page linked above and you can view all the concepts about Hadoop (it's pretty advanced though)
I'm pretty sure this isn't what you were looking for but I've no idea what you want so at least I hope you can check a few new projects that may help.
also check Storm: https://github.com/nathanmarz/storm it's not related to Hadoop but works on realtime scenarios which Hadoop is not suited for.
