  Cloud computing is gradually gaining popularity among businesses due to its
distinct advantages over self-hosted IT infrastructures. Business Intelligence
(BI) is a highly resource intensive system requiring large-scale parallel
processing and significant storage capacities to host data warehouses. In
self-hosted environments it was feared that BI will eventually face a resource
crunch situation because it will not be feasible for companies to keep adding
resources to host a neverending expansion of data warehouses and the online
analytical processing (OLAP) demands on the underlying networking. Cloud
computing has instigated a new hope for future prospects of BI. However, how
will BI be implemented on cloud and how will the traffic and demand profile
look like? This research attempts to answer these key questions in regards to
taking BI to the cloud. The cloud hosting of BI has been demonstrated with the
help of a simulation on OPNET comprising a cloud model with multiple OLAP
application servers applying parallel query loads on an array of servers
hosting relational databases. The simulation results have reflected that true
and extensible parallel processing of database servers on the cloud can
efficiently process OLAP application demands on cloud computing. Hence, the BI
designer needs to plan for a highly partitioned database running on massively
parallel database servers in which, each server hosts at least one partition of
the underlying database serving the OLAP demands.
