[DOCS-13557, DOCS-13567] Fix rollup wording and clarify distribution histogram types

content/en/dashboards/functions/rollup.md

@@ -1,6 +1,6 @@
 ---
 title: Rollup
-description: Control time aggregation and data point intervals using custom rollup functions and moving rollups for metrics.
+description: Control time aggregation and datapoint intervals using custom rollup functions and moving rollups for metrics.
 aliases:
     - /graphing/functions/rollup/
 further_reading:
@@ -12,7 +12,7 @@ further_reading:
 Every metric query is inherently aggregated. However, appending the `.rollup()` function at the end of a query allows you to perform custom [time aggregation][1] that overrides the defaults. This function enables you to define:
 
 * The rollup `<interval>`: the interval of time your data is aggregated over ([if larger than the query-enforced rollup interval](#rollup-interval-enforced-vs-custom)).
-* The rollup `<aggregator>`: How your data points are aggregated within a given rollup time interval.
+* The rollup `<aggregator>`: How your datapoints are aggregated within a given rollup time interval.
 
 To apply a rollup, navigate to the **Add function** (Σ) button of the graphing editor: 
 
@@ -24,8 +24,8 @@ The function takes two parameters, `<AGGREGATOR>` and optionally `<INTERVAL>`: `
 
 | Parameter  | Description                                                                                                     |
 |------------|-----------------------------------------------------------------------------------------------------------------|
-| `<AGGREGATOR>` | Can be `avg`, `sum`, `min`, `max`, or `count`, and defines how data points are aggregated within a given time interval. [Enforced default](#rollup-interval-enforced-vs-custom): `avg`. |
-| `<INTERVAL>`   | Time (in seconds) of the interval between two data points displayed. Optional.                                            |
+| `<AGGREGATOR>` | Can be `avg`, `sum`, `min`, `max`, or `count`, and defines how datapoints are aggregated within a given time interval. [Enforced default](#rollup-interval-enforced-vs-custom): `avg`. |
+| `<INTERVAL>`   | Time (in seconds) of the interval between two datapoints displayed. Optional.                                            |
 
 You can use them individually or together, for instance `.rollup(sum,120)`. The following bar graph displays a week's worth of CPU usage for a host **without** using the `.rollup()` function:
 
@@ -43,13 +43,13 @@ The following bar graph displays the same metric, graphed using a day-long rollu
 | `moving_rollup` | Rollup to combine the points in the last X seconds. | `moving_rollup(<METRIC_NAME>, <INTERVAL> , <AGGREGATOR>)` |
 
 
-Applying the `moving_rollup()` function to a query allows you to combine points from the most recent specified time range—that is, the last X seconds. Like with `.rollup()`, `<AGGREGATOR>` can be `sum`/`min`/`max`/`count`/`avg` and defines how data points are aggregated within the given time interval.
+Applying the `moving_rollup()` function to a query allows you to combine points from the most recent specified time range—that is, the last X seconds. Like with `.rollup()`, `<AGGREGATOR>` can be `sum`/`min`/`max`/`count`/`avg` and defines how datapoints are aggregated within the given time interval.
 
 ## Rollup interval: enforced vs custom
 
 When graphing, Datadog sets a limit on the number of points per timeseries. To retain visual clarity, a series can have up to 1500 points. To respect this limit, Datadog rolls up datapoints automatically, defaulting to the `avg` method, effectively displaying the average of all datapoints within a time interval for a given metric. The default rollup time interval varies depending on how the data is visualized. See the following chart to reference these default time intervals:
 
-| Timeframe           | Rollup Interval, Line Graph | Rollup Interval, Bar Graph | Rollup Interval, API |
+| Time frame          | Rollup Interval, Line Graph | Rollup Interval, Bar Graph | Rollup Interval, API |
 |---------------------|-----------------------------|----------------------------|----------------------|
 | The past hour       | 20s                         | 1m                         | 20s                  |
 | The past four hours    | 1m                          | 2m                         | 1m                   |
@@ -58,7 +58,7 @@ When graphing, Datadog sets a limit on the number of points per timeseries. To r
 | The past week       | 1hr                         | 2hr                        | 1hr                  |
 | The past month      | 4hr                         | 12hr                       | 4hr                  |
 
-A custom `.rollup()` function can be used to enforce the type of time aggregation applied (`avg`, `min`, `max`, `count`, or `sum`) and optionally the time interval to rollup. Using this function, you can set the rollup time interval to a different value than the defaults, up to a limit of 1500 points. This supports up to one point per minute over a day.
+A custom `.rollup()` function can be used to specify the type of time aggregation applied (`avg`, `min`, `max`, `count`, or `sum`) and optionally the time interval to rollup. Using this function, you can set the rollup time interval to a different value than the defaults, up to a limit of 1500 points. This supports up to one point per minute over a day.
 
 **Note**: Queries for `COUNT` and `RATE` type metrics have the `.as_count()` modifier appended automatically in the UI, which sets the rollup method used to `sum` and disables interpolation. This `.as_count()` is explicitly visible at the end of the query:
 

content/en/dashboards/widgets/distribution.md

@@ -22,7 +22,7 @@ further_reading:
   text: "Querying"
 ---
 
-The Distribution visualization shows data aggregated across one or several tags, such as *hosts*. Unlike the [heatmap][1], a distribution graph's x-axis is quantity rather than time.
+The Distribution visualization shows data aggregated across one or several tags, such as *hosts*. Unlike the [heat map][1], a distribution graph's x-axis is quantity rather than time.
 
 This visualization displays only a single query; additional queries are disregarded.
 
@@ -34,20 +34,29 @@ This visualization displays only a single query; additional queries are disregar
 
 ### Configuration
 
-1. Choose the data to graph.The Distribution visualization supports metrics, live processes, APM request latency, log events, and RUM events.
-**Note**: This visualization type is useful only when data is aggregated across tag keys, such as for each `host`.
-1. Make a selection in the "`avg`/`max`/`min`/`sum by`/" control to see your data across the associated tags.
+1. Choose the data to graph. The Distribution visualization supports metrics, live processes, APM request latency, log events, and RUM events.
+   **Note**: This visualization type is useful only when data is aggregated across tag keys, such as for each `host`.
+1. Make a selection in the `avg`/`last`/`max`/`min`/`sum` control to see your data across the associated tags.
 1. Customize your graph with the available options.
 
 ### Options
 
+#### Histogram of points vs. histogram of groups
+
+The Distribution widget supports two histogram types:
+
+- **Histogram of points**: Each individual datapoint (for example, a raw request latency measurement) contributes to a bucket based on its value. Use this when you want to see the full distribution of measurements across all recordings.
+- **Histogram of groups**: Each group (such as a service or host) is first reduced to a single aggregated value (for example, the p75 latency), and then those aggregated values are distributed across buckets. The resulting shape reflects the spread of per-group summary values, not individual measurements.
+
+**Note**: Because these two types aggregate data differently, switching between them can significantly change the shape of the histogram.
+
 #### Percentile markers
 
 With APM request distributions, you can add percentile markers on the x-axis.
 
 {{< img src="dashboards/widgets/options/distribution_marker_controls.jpg" alt="Marker control preferences" style="width:80%;">}}
 
-#### X-axis and Y-axis controls
+#### X-axis and y-axis controls
 
 Axis controls are available through the UI and the JSON editor.