Query Performance Tuning - Expert Cube Development with SSAS Multidimensional Models - page 208

It might seem like query binding is the easiest way to filter your data, and while
it's the most widely-used approach it does have one serious shortcoming. Since it
involves hard-coding a SQL SELECT statement into the definition of the partition,
any change to your fact table such as the deletion or renaming of a column can mean
the SELECT statement produces error when it is run, and this means the partition
processing will fail. If you have a lot of partitions in your measure group - and it's
not unusual to have over one hundred partitions on a large cube - altering the query
used for each one is somewhat time-consuming. Instead, binding a partition to a
view in your relational database will make this kind of maintenance much easier,
although you do of course now need to generate one view for each partition.
It's very important that you check the queries you're using to filter your
fact table for each partition. If the same fact table row appears in more
than one partition, or if fact table rows don't appear in any partition,
this will result in your cube displaying incorrect measure values.
On the Processing and Storage Locations step of the wizard you have the chance to
create the partition on a remote server instance, functionality that is called Remote
Partitions. This is one way of scaling out Analysis Services: you can have a cube and
measure group on one server but store some of the partitions for the measure group
on a different server, something like a linked measure group but at a lower level. It
can be useful for improving processing performance in situations when you have a
very small time window available for processing but in general we recommend that
you do not use remote partitions. They have an adverse effect on query performance
and they make management of the cube (especially backup) very difficult.
Also, on the same step you have the chance to store the partition at a location other
than the default of the Analysis Services data directory. Spreading your partitions
over more than one volume may make it easier to improve the IO performance of
your solution, although again it can complicate database backup and restore.