> ## Documentation Index
> Fetch the complete documentation index at: https://docs.revenuebase.ai/llms.txt
> Use this file to discover all available pages before exploring further.
# AWS S3 setup
> Grant your AWS account access to the RevenueBase S3 bucket and start loading your data files.
export const RBCardGroup = ({cols = 3, children}) =>
}
{tag && {tag}}
;
};
RevenueBase delivers data to a managed S3 bucket and grants your AWS account read access. Data is available in **CSV**, **JSON**, and **Parquet** formats — you get all three with every delivery. Each monthly delivery lands in a new date-stamped folder; previous deliveries are never overwritten.
***
## Setup your AWS S3 integration
On the RevenueBase web application, select `Integrations` from the side bar.
Under `Step 1 — Your AWS details`, submit your AWS Account ID.
You can find your AWS Account ID in the top-right dropdown of the AWS Console, or by running `aws sts get-caller-identity` in the AWS CLI.
Once your AWS Account ID has been submitted, please allow up to 24 hours as we prepare to provision your S3 buckets. Once provisioned, you will receive an email including your bucket ARN, region, access details, and a step-by-step setup guide.
Once your S3 bucket is provisioned, test your connection using the AWS CLI:
```bash theme={null}
aws s3 ls s3://// \
--request-payer requester \
--region
```
You can also access via ARN:
```bash theme={null}
aws s3 ls s3://arn:aws:s3:::accesspoint/// \
--request-payer requester \
--region
```
Use the **AWS CLI** — not the AWS Console web UI — to access RevenueBase buckets. The Console does not support `--request-payer` and will return access errors.
***
## Bucket structure
Your data lives in date-stamped folders within the S3 bucket. The path structure is:
```
///
```
| Path segment | Description |
| --------------- | --------------------------------------------------------------------------------------- |
| `delivery_date` | Date of delivery in `YYYYMMDD` format (e.g., `20260201`) |
| `dataset_name` | The dataset included in your subscription (e.g., `per`, `org`, or a pre-joined dataset) |
| `file_format` | One of `json`, `csv`, or `parquet` |
For more on Parquet, see the official Parquet documentation.
Data is split across multiple files within each delivery folder. This is by design — it enables parallel processing and significantly improves import performance for large datasets.
***
## Next Steps
Before writing queries, read Data Freshness & Quality to understand `EMAIL_LAST_VERIFIED_AT`, sparse profiles, and the monthly verification cadence.
Under `Step 1 — Your AWS details`, submit your AWS Account ID.
