What is a Data Share?
A data share is a mechanism for accessing external datasets directly within your data warehouse environment. Instead of receiving data through file transfers, APIs, or ETL pipelines, data shares appear as read-only tables in your warehouse that you can query alongside your own data. The tables remain stored in Aampe’s infrastructure but are queryable from your environment. Key Characteristics:- No ETL Latency - Data refreshes in real-time as production systems update
- Easy Access - Tables appear directly in your warehouse environment as read-only objects
- No Storage Costs - You’re responsible only for compute resources used when querying. There are no ingestion or storage costs.
What Data Does Aampe Share?
See our page with detailed table and column descriptions.How Do I Activate Data Sharing?
Contact your Aampe representative to turn on a data share. For Google BigQuery, create a service account in your project and send us the email. The steps are on the BigQuery page. Once the share is active, the tables appear in your project as read-only. You can join them with your own data using standard SQL.Supported Destinations
- Amazon S3
- Azure Blob Storage
- Google Cloud Storage
- Amazon Redshift
- Google BigQuery
- Databricks
- Snowflake
Change Management
Data Share FAQs
How often do the tables update?
How often do the tables update?
The tables update daily.
How are the user propensities computed?
How are the user propensities computed?
For each user, we simulate hundreds of future potential messages given the current Bayesian priors for each label. We repeat this process for value propositions, offerings, tone, etc. and then report the percent of messages with each label.