"However, when you start to look at much larger datastores such as data warehousing, reporting and analytics and streaming data, normalisation will often become a hinderence to the working of the database."

Well, sure, but can you be a little more specific? I always gathered that a typical datawarehouse is a collection of "star" schemas, with one, typically narrow but deep fact table that has references to the rather wide but *relatively* shallow dimension tables. The dimension tables are denormalized, and highly redundant, and can contain aggregates, but the fact table usually does not have redundancy or aggregation.

Is it the denormalisation of these star schema dimension tables you are referring too (in favour of the more normalized dimension tables in "snowflake" schemas)? Or are you recommending to have denormalized fact tables ? That would be very interesting indeed, and I would like hear more about that.