# Waste Reduction

Seemore continuously analyzes your Snowflake environment to surface concrete savings opportunities across storage, compute, and licensing. Each insight includes estimated annual savings so you can prioritize high-impact actions.

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## Orphan Tables

Tables and views with **no pipeline connections and zero query activity** over the analysis window. Dropping them reclaims storage and reduces clutter.

{% content-ref url="waste-reduction/orphan-tables" %}
[orphan-tables](https://docs.seemoredata.io/external-docs/fundamentals/our-features/waste-reduction/orphan-tables)
{% endcontent-ref %}

## Unused Data Flows

Tables that are **actively written to by pipelines but never read**. The upstream pipeline spend is pure waste.

{% content-ref url="waste-reduction/unused-data-flows" %}
[unused-data-flows](https://docs.seemoredata.io/external-docs/fundamentals/our-features/waste-reduction/unused-data-flows)
{% endcontent-ref %}

## Frequency Optimization

Tables whose **write frequency far exceeds their read frequency**. Reducing refresh cadence saves compute without affecting consumers.

{% content-ref url="waste-reduction/frequency-optimization" %}
[frequency-optimization](https://docs.seemoredata.io/external-docs/fundamentals/our-features/waste-reduction/frequency-optimization)
{% endcontent-ref %}

## Inactive Users

BI platform users (Tableau, PowerBI) who have **not logged in within a configurable threshold**. Reclaiming their licenses reduces subscription costs.

{% content-ref url="waste-reduction/inactive-users" %}
[inactive-users](https://docs.seemoredata.io/external-docs/fundamentals/our-features/waste-reduction/inactive-users)
{% endcontent-ref %}

## Compute Idle Optimization

Warehouses kept alive by **high-frequency queries that prevent auto-suspend**. Reducing query frequency or adjusting auto-suspend settings reclaims idle compute spend.

{% content-ref url="waste-reduction/compute-idle-optimization" %}
[compute-idle-optimization](https://docs.seemoredata.io/external-docs/fundamentals/our-features/waste-reduction/compute-idle-optimization)
{% endcontent-ref %}

***

## Exclude Users from Usage

Service accounts, ETL bots, and monitoring tools can generate significant query activity that inflates usage metrics. The **Exclude Users from Usage** setting lets you filter these users out of usage calculations so insights reflect real human consumption patterns.

### How to Configure

1. Navigate to **Waste Reduction → Insights Configuration** (top-right button).
2. Select the Snowflake integration you want to configure.
3. Check the users you want to exclude from usage calculations.
4. Click **Save**.

<figure><img src="https://3620459840-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FnSbIoBjUxWTGNWa9gGw7%2Fuploads%2Fgit-blob-f06141f37d14cef7650955ab5d31e8c0f5a30869%2Fexclude-users-walkthrough.gif?alt=media" alt="Walkthrough: excluding users from usage calculations"><figcaption><p>Walkthrough: excluding users from usage calculations</p></figcaption></figure>

### Which Insights Are Affected

| Insight                       | Affected? | Details                                                                                                              |
| ----------------------------- | --------- | -------------------------------------------------------------------------------------------------------------------- |
| **Orphan Tables**             | Yes       | Excluded users' queries are ignored when determining whether a table has usage.                                      |
| **Unused Data Flows**         | Yes       | Excluded users' reads are ignored, so tables read only by bots still appear as unused.                               |
| **Frequency Optimization**    | Yes       | The Snowflake queries that detect write-heavy / read-light patterns filter out excluded users.                       |
| **Inactive Users**            | No        | This insight queries BI platform login activity, not Snowflake usage.                                                |
| **Compute Idle Optimization** | No        | This insight evaluates warehouse-level uptime patterns; all query activity (including service accounts) is relevant. |

{% hint style="info" %}
Changes take effect the next time insights are recalculated (typically within 24 hours).
{% endhint %}