> For the complete documentation index, see [llms.txt](https://docs.onelens.cloud/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.onelens.cloud/optimize-cost-savings-and-recommendations/deep-insights.md).
# Deep Insights
Deep Insights breaks down service costs that are hard to read from a bill: data transfer, network flows, log ingestion and BigQuery. Each page splits a service's cost into its parts, and where OneLens finds a saving, it raises a ticket or an insight.
Go to **Optimize → Deep Insights**. The menu groups the pages by provider.
| Provider | Page | What it covers |
| ---------- | ------------------------------------ | ----------------------------------------------------------------- |
| AWS | Data Transfer Cost Reports | Data transfer cost by type, region and resource |
| AWS | VPC Flow Analysis | Traffic flows through your VPCs and what they cost |
| Azure | Azure Monitor | Log Analytics workspace cost and ingestion |
| Azure, GCP | Data Transfer Cost for Azure and GCP | Data transfer cost by type, region and resource |
| GCP | Cloud Logging | Log bucket cost and ingestion |
| GCP | BigQuery | Dataset compute and storage cost, queries, users and reservations |
### How the Azure Monitor, Cloud Logging and BigQuery pages work
These three pages share a layout.
**List page.** Cards at the top summarise the service. The table lists every workspace, log bucket or dataset. Use **Default View** to switch saved views, the search box to find a row by name, and the date range, **Export** and **Filters** to set and download the data.
In the table, **Total Cost** covers the selected date range and **Prev Cost** covers the period of the same length just before it. For example, if the range is 15 Sep to 14 Oct, Prev Cost covers 16 Aug to 14 Sep.
**Detail page.** Click a row to open it. Four cards sit at the top, followed by four tabs.
| Tab | What it shows |
| ----------------------------------------------- | ----------------------------------------------------------------------------------------------------------------------------------- |
| Resource Details (Dataset Details for BigQuery) | The resource's settings and what is connected to it |
| Cost History | <\> |
| Cost & Usage Overview | The cost split into components for the date range you pick, with the usage behind each one. Total Cost is the sum of the components |
| Tickets | Tickets raised on this resource |
The detail cards use fixed windows, such as **Last 30 Days Cost** and **Previous Month Cost**. Their figures can differ from the Total Cost and Prev Cost in the list, which follow the date range you pick.
**Tickets tab.** The Tickets tab on each list page shows **Total Tickets** and **Potential Savings (Up-To)**, along with the share of the service's cost those savings represent. The table works the same way as in Storage Optimization: change **Status** and **Assigned To** from the table, search by ticket ID, choose **Columns**, **Export**, or **Filters**.
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