At one end of the scale you have a data warehouse which is 'batch loaded' meaning jobs run to load the data. You take advantage of this specialised processing time to model and transform the data into a schema that is easy to analyse. Data warehouses are much more than just copying data around.
At the other end of the scale is what you are doing right now - performing 'federated' queries.
You need to research the advantages and disadvantages of each method and compare them to your business requirements. You also need to consider the future state of systems, i.e. maybe your program works now but what happens if data volumes increase or you suddenly need to access another five systems?
For example, is it OK if your users have data which is one day out of date (Latency)? Will this still be OK in 5 years?
In answer to your questions:
1) Do you copy all the data needed to make a decision into the Data Warehouse?
If your users can put up with latency, and you have enough disk space, and smart enough replication (i.e. CDC), and adhoc querying of the source system is an issue, then yes you would copy all the data over. (into something that is usually called an ODS)
2) What do you use as the user interface?
Since you have already mentioned SSIS (a MS tool), note that MS also comes with SSAS (a cube building tool), SSRS (a web report tool) and Excel (basically your cube client). You can wrap this up in Sharepoint but it's not trivial.
Note that all these functions (ETL, Cubing, User Interface) are provided by many other vendors as well, but in a MS shop you have basically already bought your BI tools so you might want to start with those.
You can use .Net to build yourself a more sophisiticated tool but you are better off getting something off the shelf.