DataShovel (DS) is the next generation data warehouse automation tool built for the cloud. DS speeds up DataVault modelled data warehouse projects, forces same conventions to all the developers, reduces bugs and improves documentation. DS project starts with visual modelling of the data warehouse with DataVault method.

If you are building DataVault data warehouse on top of Azure, you need DataShovel.

DS has solid background in decades of data warehouse development and previous generations of the automation tools.

Following steps are required to build solutions with DataShovel:

1) Define the naming conventions and other configurable settings in the project - or accept the provided defaults

2) Build the DataVault data model with visual canvas

3) Connect to the source data to get the tales, columns and metadata (names, data types etc) from the source systems

4) Map together the data sources and data model fields and tables

5) In the background DS populates automatically:

- Staging loads from source to staging area - including the table generations

- The actual data warehouse tables and columns into the database

- ELT orchestrations to the orchestration tool - native integration with Azure DataFactory v2

In other words, DS is a code generator and provides a customer minimal vendor lock.

Supported platforms for data warehouse databases:

- Azure Synapse Analytics

- Azure SQL db

- Snowflake

DS is not only a tool for data warehouse developers. It is also a tool for

- Customer key users - DS generates automatically data lineage and works as automatic documentation of the data flow

- Customer DW developers - advanced customers may  gain from the possibility for the customer users to make changes to data warehouse structures