update s3 guide with describe

docs/integrations/data-ingestion/s3/index.md

@@ -29,8 +29,67 @@ Using wildcards in the path expression allow multiple files to be referenced and
 
 ### Preparation {#preparation}
 
-To interact with our S3-based dataset, we prepare a standard `MergeTree` table as our destination. The statement below creates a table named `trips` in the default database:
+Prior to creating the table in ClickHouse, you may want to first take a closer look at the data in the S3 bucket. You can do this directly from ClickHouse using the `DESCRIBE` statement:
 
+```sql
+DESCRIBE TABLE s3('https://datasets-documentation.s3.eu-west-3.amazonaws.com/nyc-taxi/trips_*.gz', 'TabSeparatedWithNames');
+```
+
+The output of the `DESCRIBE TABLE` statement should show you how ClickHouse would automatically infer this data, as viewed in the S3 bucket. Notice that it also automatically recognizes and decompresses the gzip compression format:
+
+```sql
+DESCRIBE TABLE s3('https://datasets-documentation.s3.eu-west-3.amazonaws.com/nyc-taxi/trips_*.gz', 'TabSeparatedWithNames') SETTINGS describe_compact_output=1
+
+┌─name──────────────────┬─type───────────────┐
+│ trip_id               │ Nullable(Int64)    │
+│ vendor_id             │ Nullable(Int64)    │
+│ pickup_date           │ Nullable(Date)     │
+│ pickup_datetime       │ Nullable(DateTime) │
+│ dropoff_date          │ Nullable(Date)     │
+│ dropoff_datetime      │ Nullable(DateTime) │
+│ store_and_fwd_flag    │ Nullable(Int64)    │
+│ rate_code_id          │ Nullable(Int64)    │
+│ pickup_longitude      │ Nullable(Float64)  │
+│ pickup_latitude       │ Nullable(Float64)  │
+│ dropoff_longitude     │ Nullable(Float64)  │
+│ dropoff_latitude      │ Nullable(Float64)  │
+│ passenger_count       │ Nullable(Int64)    │
+│ trip_distance         │ Nullable(String)   │
+│ fare_amount           │ Nullable(String)   │
+│ extra                 │ Nullable(String)   │
+│ mta_tax               │ Nullable(String)   │
+│ tip_amount            │ Nullable(String)   │
+│ tolls_amount          │ Nullable(Float64)  │
+│ ehail_fee             │ Nullable(Int64)    │
+│ improvement_surcharge │ Nullable(String)   │
+│ total_amount          │ Nullable(String)   │
+│ payment_type          │ Nullable(String)   │
+│ trip_type             │ Nullable(Int64)    │
+│ pickup                │ Nullable(String)   │
+│ dropoff               │ Nullable(String)   │
+│ cab_type              │ Nullable(String)   │
+│ pickup_nyct2010_gid   │ Nullable(Int64)    │
+│ pickup_ctlabel        │ Nullable(Float64)  │
+│ pickup_borocode       │ Nullable(Int64)    │
+│ pickup_ct2010         │ Nullable(String)   │
+│ pickup_boroct2010     │ Nullable(String)   │
+│ pickup_cdeligibil     │ Nullable(String)   │
+│ pickup_ntacode        │ Nullable(String)   │
+│ pickup_ntaname        │ Nullable(String)   │
+│ pickup_puma           │ Nullable(Int64)    │
+│ dropoff_nyct2010_gid  │ Nullable(Int64)    │
+│ dropoff_ctlabel       │ Nullable(Float64)  │
+│ dropoff_borocode      │ Nullable(Int64)    │
+│ dropoff_ct2010        │ Nullable(String)   │
+│ dropoff_boroct2010    │ Nullable(String)   │
+│ dropoff_cdeligibil    │ Nullable(String)   │
+│ dropoff_ntacode       │ Nullable(String)   │
+│ dropoff_ntaname       │ Nullable(String)   │
+│ dropoff_puma          │ Nullable(Int64)    │
+└───────────────────────┴────────────────────┘
+```
+
+To interact with our S3-based dataset, we prepare a standard `MergeTree` table as our destination. The statement below creates a table named `trips` in the default database. Note that we have chosen to modify some of those data types as inferred above, particularly to not use the [`Nullable()`](https://clickhouse.com/docs/en/sql-reference/data-types/nullable) data type modifier, which could cause some unnecessary additional stored data and some additional performance overhead:
 
 ```sql
 CREATE TABLE trips