📄️ Overview
A data warehouse is a data source that contains the tables and views that you import as fact datasets and dimension datasets into AtScale models. It also contains aggregate-table instances that either you or the AtScale engine creates in a schema that you specify.
📄️ About Data Warehouse Security
You can configure which users and groups have access to each of your data warehouses. These permissions apply across AtScale. If a user has access to a data warehouse, they can do the following:
📄️ Data Warehouse Preparation
Complete the following data warehouse configuration steps before
📄️ Adding Databricks Data Warehouses
A Databricks data warehouse contains the tables and views that you want
📄️ Adding Google BigQuery Data Warehouses
A Google BigQuery data warehouse is an instance of Google BigQuery that contains the tables and views that you want to access as model facts and dimensions. It also contains aggregate table instances that either you or the AtScale engine creates in a BigQuery dataset that you specify.
📄️ Setting Up Impersonation for Google BigQuery
If you are using Google BigQuery as a data warehouse and Google G Suite
📄️ Adding InterSystems IRIS Data Warehouses
An InterSystems IRIS data warehouse contains the tables and views that
📄️ InterSystems IRIS: Customer-Managed UDAF Installation
When setting up an InterSystems IRIS Data Warehouse, you must choose
📄️ Adding Snowflake Data Warehouses
A Snowflake data warehouse is a cloud-based data warehouse that contains
📄️ Adding PostgreSQL Data Warehouses
A PostgreSQL data warehouse contains the tables and views that you want
📄️ Adding Amazon Redshift Data Warehouses
An Amazon Redshift data warehouse is an Amazon Redshift cluster and database that contains the tables and views that you want to access as model facts and dimensions. It also contains aggregate table instances that either you or the AtScale engine creates in a schema that you specify.
📄️ Configuring Query Mapping
If you have multiple connections for the same type of data warehouse,