diff --git a/content/docs/(documentation)/query-data/datasets.mdx b/content/docs/(documentation)/query-data/datasets.mdx
index ee7ee65a..26fb8956 100644
--- a/content/docs/(documentation)/query-data/datasets.mdx
+++ b/content/docs/(documentation)/query-data/datasets.mdx
@@ -46,6 +46,16 @@ On the right, you see the following:
 - [Saved queries](#saved-queries)
 - [Query history](#query-history)
 
+### Explore metrics datasets
+
+When you select a metrics dataset, Axiom displays the list of metrics in the dataset instead of a list of fields. Each row displays the type, the name, and the unit of the metric.
+
+Axiom displays the unit of a metric in one of the following ways:
+
+- Units without braces are standard [UCUM](https://ucum.org/) units that Axiom recognizes and displays as readable labels. For example, a metric ingested with the unit `By` appears as `bytes`, and a metric ingested with the unit `ms` appears as `milliseconds`. The dimensionless unit `1` appears as `dimensionless`.
+- Units in curly braces are values that Axiom doesn’t translate. These are UCUM annotations like `{requests}` or unit values that aren’t valid UCUM units. Axiom displays the value inside braces as it was ingested.
+- Empty braces (`{}`) mean that unit information isn’t available for the metric. This happens when the metric was ingested without a unit or when the unit of the metric isn’t consistent within the selected time range.
+
 ### Edit field
 
 To edit a field:
diff --git a/content/docs/(documentation)/query-data/metrics.mdx b/content/docs/(documentation)/query-data/metrics.mdx
index fb6651f3..51fdf77a 100644
--- a/content/docs/(documentation)/query-data/metrics.mdx
+++ b/content/docs/(documentation)/query-data/metrics.mdx
@@ -138,7 +138,6 @@ MetricsDB applies the following transformations to improve query performance and
 
 - **Timestamp precision**: Truncate nanosecond timestamps to second precision. MetricsDB is built for use cases where second-level granularity is sufficient, and this optimization significantly improves compression ratios and query speed.
 - **Unified tag namespace**: Flatten resource, scope, and metric tags into a single namespace. This simplification makes queries more straightforward and enables faster dimensional filtering. You don’t need to remember which tags came from which scope.
-- **Unit normalization**: Convert the `unit` attribute to `otel.metric.unit` for consistent handling across all metric types.
 - **Histogram handling**: Assume equal-width histograms and don’t preserve histogram metadata. This trade-off supports the most common histogram analysis patterns (percentiles, distribution visualization) while reducing storage requirements.
 
 These design choices reflect real-world metrics usage patterns. If your use case requires capabilities not currently supported, [contact Axiom](https://axiom.co/contact) to discuss your requirements. Your feedback helps shape MetricsDB’s evolution.