What is data warehouse automation?
Data warehouse automation streamlines the continuous centralization of data from varied sources into one place and into one consolidated data model, to facilitate analysis and reporting.
Data warehouse automation
Data warehouse automation (DWA) is replacing standard methods for building data warehouses. It automates the planning, modeling, and integration steps to keep pace with an ever-increasing amount of data and sources.
Data warehouse automation is crucial for standardizing the way data — from many sources and in many formats — is integrated and woven together into a consolidated view. Teams increase productivity, agility, and the quality of their output.
Introducing Data Vault automation
The Data Vault 2.0 data model is rapidly becoming the DWA standard. Its simple design architecture makes it much easier to streamline processes and meets both data engineers' and compliance and audit departments' needs.
- Source data is copied to and stored, over time, in a single data warehouse. Values can always be traced back to the source.
- Modeling breaks down and consolidates source data into three core components: hubs (unique entities important to the business such as ‘customer’, ‘product’, ‘store’), links (relationships between entities), and satellites (all the properties and history of an entity).
Organizations use a variety of tools to process and manage data. Data Vault automation also supports the automated build of a data hub, data lake, data lakehouse and data mesh.