update types

Author: kschlarman

docs/integrations/data-ingestion/clickpipes/kafka/04_best_practices.md

@@ -139,8 +139,8 @@ Benchmark details:
 - We used production ClickHouse Cloud services with enough resources to ensure that throughput was not bottlenecked by the insert processing on the ClickHouse side.
 - The ClickHouse Cloud service, the Kafka cluster (Confluent Cloud), and the ClickPipe were all running in the same region (`us-east-2`).
 - The ClickPipe was configured with a single replica.
-- The sample data included nested data with a mix of uuid, string, and integer datatypes.
-  - Other datatypes, such as floats may be less performant.
+- The sample data included nested data with a mix of UUID, String, and Int datatypes.
+  - Other datatypes, such as Floats, Decimals, and DateTime types may be less performant.
 - There was no appreciable difference in performance between compressed and uncompressed data.