Quick Start
Get your first automated data delivery running in five steps.
Prerequisites
- A DataDrop account (sign up at the landing page)
- Credentials for at least one data warehouse
- An S3 bucket where DataDrop can write exported files
- An IAM role that grants DataDrop access to the S3 bucket
Setup Steps
Create a Client
Navigate to Clients and click "Add Client". Enter the client name, service tier, and optional contract details. Each client represents an organization you deliver data to.
Connect a Warehouse
Go to the client's Warehouses tab and click "Add Connection". Select your warehouse type (Snowflake, Redshift, PostgreSQL, Databricks, or BigQuery) and enter your credentials. You'll also configure the S3 bucket where exported files will be written.
Warehouse setup guides →Create a Report
Go to the client's Reports tab and click "Add Report". Choose the warehouse connection, specify the source schema and table (or a custom SQL query), pick your file format (Parquet or CSV), and set a delivery schedule.
Report configuration guide →Trigger a Delivery
Click the "Cook Now" action on any report to trigger an on-demand delivery run. DataDrop will export the data, compute diffs against the previous delivery, generate an AI narrative, and write the file to S3.
Add Contacts & Notifications
Add email contacts to the client. When a delivery completes, DataDrop sends a notification email with a summary and a secure download link. You can also configure a Slack webhook on each report for team notifications.
What Happens During a Run
- Export — DataDrop connects to your warehouse, runs the query, and writes the result to S3 in your chosen format.
- Receipt — A delivery receipt is generated with row counts, file size, and schema details.
- Diff — The current delivery is compared against the previous one to detect added, removed, and changed rows.
- Narrative — An AI-generated summary describes what changed in plain English.
- Notify — Email and Slack notifications are sent with the summary and a download link.