Most of the complexity of needing Data.Dynamic has to do with the way we store the heterogeneous collection that is our observed data. There is a nicer way to do this which I hope lands in a future release.
A while ago I tried to port some of the Python code from the book Programming Collective Intelligence to Haskell, and I got stuck on the seemingly simple problem of reading and processing heterogenous collections (strings and numbers).
So I don't really consider myself a Haskell programmer, but the standard advice is to think about operation you are going to perform on those strings and numbers later, then think if there is a datatype you could create instead.
As an example, suppose I am trying to load a csv file with two fields being strings and one being Double. A list of lists representation isn't going to cut it. Instead I should make a Row datatype
Then you can parse the csv file into a [Row] representation.
As an aside, if the task did involve parsing csv I suggest the cassava library which I found out about through the amazing What I Wish I Knew When Learning Haskell (http://dev.stephendiehl.com/hask/)
data Datum = S String | D Double
lst :: [Datum]
lst = [S "a", D 3.14]
In Python we'd have to write the logic to handle both cases and fail with an exception or do an instanceof check. In Haskell we'd do this by pattern matching on the sum type.
case (lst !! 42) of
S n -> -- handle string
D n -> -- handle number