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@alai97 alai97 commented Oct 9, 2025

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We aim to merge PRs within one week or less, but delays happen sometimes.

If your PR is open longer than two weeks without any human activity, please tag a code owner in a comment.

PRs must meet these requirements to be merged:

  • Successful preview build.
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  • Release notes/new features docs: Feature/version released to at least one prod environment.

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A few nits around style guide adherence and strongly tab usage for less toil for users and sharability.

@alai97 alai97 requested a review from pratmit as a code owner October 15, 2025 02:22
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Checked the preview, the 'Connect your Data Warehouse items are empty'
Consider the DMS component for these to keep the content contained to one page: https://harness.atlassian.net/wiki/spaces/HDH/pages/22466920790/Dynamic+Markdown+Selector+Component

warehouse-native-experiments.mp4

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Approving with the understanding that we flesh out the empty "Connect your Data Warehouse" items in a subsequent PR.

Otherwise, looks great.

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| **Example Raw Schema** | **Transformations** |
| --------------------------------------------------------------------------------------------------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `account_id` <br /> `metric_type` <br /> `metric_value` <br /> `created_at` | • Map `account_id``user_id`. <br /> • Map `metric_type``event_name`. <br /> • Standardize `metric_value``event_value`. |
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"Map account_id --> key"

mapping account to user may be confusing here, we just want them to identify it as the generic unique ID

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Suggested change
| `account_id` <br /> `metric_type` <br /> `metric_value` <br /> `created_at` | • Map `account_id``user_id`. <br /> • Map `metric_type``event_name`. <br /> • Standardize `metric_value``event_value`. |
| `account_id` <br /> `metric_type` <br /> `metric_value` <br /> `created_at` | • Map `account_id``key`. <br /> • Map `metric_type``event_name`. <br /> • Standardize `metric_value``event_value`. |

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We don't support dimensional analysis for WHN yet, so we may want to take this part out

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Remove mentions of metrics impact tab

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Let's remove this from the WHN section because we don't support dimensional analysis yet

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Remove metrics impact mentions

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A metric measures [events](/docs/feature-management-experimentation/experimentation/events/) that are sent to Harness FME. Metrics can be defined to count the occurrence of events, measure event values, or measure event properties.

Metric results are calculated for each treatment of a feature flag that shares the same traffic type as the metric and has a percentage targeting rule applied. Impact can be calculated between a selected comparison treatment and baseline treatment within a feature flag. Results are displayed on the [Metrics impact tab](https://help.split.io/hc/en-us/articles/360020844451) of the feature flag.
Metric results are calculated for each treatment of a feature flag that shares the same traffic type as the metric and has a percentage targeting rule applied. Impact can be calculated between a selected comparison treatment and baseline treatment within a feature flag. Results are displayed on the [Metrics impact tab](/docs/feature-management-experimentation/experimentation/experiment-results/viewing-experiment-results/metrics-impact-cards) of the feature flag.
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Suggested change
Metric results are calculated for each treatment of a feature flag that shares the same traffic type as the metric and has a percentage targeting rule applied. Impact can be calculated between a selected comparison treatment and baseline treatment within a feature flag. Results are displayed on the [Metrics impact tab](/docs/feature-management-experimentation/experimentation/experiment-results/viewing-experiment-results/metrics-impact-cards) of the feature flag.
Metric results are calculated for each treatment of a feature flag that shares the same traffic type as the metric and has a percentage targeting rule applied. Impact can be calculated between a selected comparison treatment and baseline treatment within a feature flag.

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4 participants