How to architect an analytical BI platform? I am working on a new BI project for a medium sized corporation. Right now there is no Analytical infrastructure in place and the reporting is done manually in Excel. There are a few different data sources (from different systems like Billing) that need to be integrated to perform the reporting and analytics. Some of them are data dumps that need some custom conversions to get into a database ready form. These have a large number of columns. These need to be processed, required columns filtered and aggregations done etc. Typically there's about 50 GB of data produced daily and will be inserted to the existing tables each day. 

We've identified that an analytical database like Vertica can be worth looking into. We don't have any prior experience with non-OLTP databases. My understanding is that Vertica (and other like it) are read-optimised and good for analytical tasks. My question is how does it fair at the initial stage where the raw data are loaded and processed? Should we use a traditional OLTP database like Oracle for that and then use the Vertica for Star Schema, Dimensional modelling type datastore? Is Vertica suited for ETL scenarios?

How is a typical architecture of this kind of scenario?
With respect to your question about using Vertica during the ETL, it's very rarely necessary (although not unknown) to use a different type of database for the ETL.  I would not do that unless you perceive a specific need to do so.  The only times I've ever heard of this being done due to interactions with legacy data sources.  Although @Kermit works with Vertica and will be more familiar with the platform, I don't see any reason to assume you need another DBMS platform for your ETL.

The reason Vertica and other systems are ill suited to transactional applications is that they use data structures that are fast to read from and batch load, but have a significant overhead per load operation.  A batched ETL process that requires index rebuilds or other such operations will be a non-issue on these systems.  The operations are too expensive for a high-volume OLTP platform but will not be too slow for a batched ETL job.

A common architecture used in telcos and other VLDB shops is to use flat files for intermediate storage and then load into the database.  Ab Initio and Ascential Datastage are tools that are designed to work in this way and this type of architecture is common on telcos.  However, ETL tools tend not to support complex transformations well, so you may well end up with a layer of data manipulation taking place within the database.

All VLDB platforms are expensive, and some are tied to proprietary hardware.  Be prepared to spend up big on your server.  3 years data at 50GB/day is around 50TB, which is getting into the region where you would need specialised kit to perform well on these data volumes.