Optimal Data Engine Version 2 is now available for download from GitHub! Here’s what it means for you.
The biggest change with the most impact is a new flag for Data Vault retired objects. The general rule is, once something gets into the Data Vault, it never goes out. But sometimes Data Vault objects are get replaced by newer versions, or even some ensembles get redesigned with new requirements. In this case, we want to keep an old version for the history, but flag it for business intelligence developers as a retired object. That simple. And, of course, we identified and fixed a few minor bugs.
Optimal Data Engine (ODE) is an open source application that can be used to build an automated data warehouse environment. The core of ODE is built around the Data Vault approach. Currently, ODE runs on MS SQL Server.

The objective of ODE is to minimise the effort required to building a Data Vault. The Data Vault methodology is based on the Ensemble modelling approach. An Ensemble is defined by the following three type of tables:

• Hub; storage for business key
• Satellite; storage for the group of attributes
• Link; a relationship between business entities.

The structured nature of Data Vault enables an automated approach. This is why we developed ODE.
We have posted the latest ODE code to the GitHub. Anyone can download it and start implementing a robust Data Warehouse of any size. Also, anyone who wants to add a feature to ODE can fork the project and contribute to it.

We keep our documentation updated on the ODE.ninja website. Here you can find manuals, development tips, code samples to help deal with Configuration, and other interesting content. Also, you can ask us a question if you want, our ODE team is happy to help!
Why a new version? Version 1 was an initial version for download. We installed this version on a client’s production environment; there is an actual Enterprise Data Warehouse built with ODE. That is one small step for a mankind, but one giant leap for ODE!
The biggest change with the most impact is a new flag for Data Vault retired objects. The general rule is, once something gets into the Data Vault, it never goes out. But sometimes Data Vault objects are get replaced by newer versions, or even some ensembles get redesigned with new requirements. In this case, we want to keep an old version for the history, but flag it for business intelligence developers as a retired object. That simple. And, of course, we identified and fixed a few minor bugs.
Hope you enjoy a journey to automated Data Vault with us.
Masseuse of all the Data – Kate