The framework has been implemented at numerous customers – all of whom are satisfied with the set-up, time-to-market and efficiency of the solution.
Our Azure Framework is based on the end-to-end analytics reference architecture from Microsoft. This offers a strong and unified foundation of which the principles are perceived as market best practice, which makes it easier to explain, develop and transfer knowledge to the client. Furthermore, we achieve horizontal and vertical scalability as we are respecting and building upon the base principles of a data lake(house).
A set of plug-and-play components like reusable and generic pipelines, transformations and Power BI reports are immediately available to achieve a faster go-to-market.
Azure DevOps is the preferred tool for project management, version control and release management.
Using version control software is a best practice for high performing DevOps teams. Version control helps data platform team members develop faster and allows the team to preserve efficiency and agility as the team scales to include more developers. Next to this, as your pipelines become business critical, it is important to be able to track changes over these prominent workflows.
It’s powerful when you can treat data pipelines as a product. For data lifecycle management, automated deployment methods serve as a guardrail that makes it easier to test and release data to the production environment. Automated deployment ensures a stable data platform for which development cycles and new features can be introduced at a fast, iterative pace.
On every project a minimum set of networking and security settings are implemented. Furthermore, logging, reporting, and alerting will be available to monitor the end-to-end solution.
Azure Devops Wiki is used to share information with the team and project stakeholders. We bring generic documentation to facilitate a smooth hand-over and onboarding of new colleagues.
