Online D♯ Advanced BDP Developer Course


In the 4-hour on-line and public D♯ advanced training course you will expand on and sharpen your existing skills building and maintaining low-code Data Warehouses using the D♯ Toolbox.

We will meet in the Microsoft Teams online classroom, and everybody will have a personal training environment in Azure Lab Services.

Who should attend?

Data architects and BDP developers that already have completed the Intro course or have been working with D♯ in customer projects, evaluations or PoCs.


  • Recap the Intro Course tutorials 1 – 3 and self-learning tutorials 4 – 10 (1 hour)
    • Main takeaways from each tutorial
  • Design Aspects in Real-Life Situations for Well-Designed Scalable BDP’s
    • Business Key Considerations
    • Data Driven vs Business Driven Modeling. Case Project Membership.
    • Design patterns for some less-than-perfect data situations
  • The D♯ SmartEngine UI – Basic Use Cases
  • Introduction to Scripting


  • The course format is an interactive workshop with some case studies in the training environment.
  • English and Finnish (course materials are in English).
  • The course fee includes a week of access to the training environment with the full D♯ Toolbox, including modeling, automation and database tools.
  • Virtual environments can also be rented for self-service training, software evaluation and trials (PoC) after the course.


  • Take a look at the D♯ Training Program in order to understand the learning process with D♯.
  • If feasible, complete all 10 tutorials from the Intro course for the best possible starting point.
  • It is recommended that you use two monitors in order to have easy simultaneous access to both the Teams presentation and the training environment.

About The Instructor

Kim is a software developer at heart, thrown into the zero-reusability world of Data Warehousing in the turn of the century. Before Data Warehouse Automation even had a name, Kim had implemented an automated DW tool that went into production as early as 2006, gaining Data Vault support in 2009, including both automatic DV structure and load procedure generation using only a conceptual model as input. Kim is all for not doing unnecessary manual work, and believes in developing automation in order to both make life easier for developers as well as standardizing the automated end result. Kim also enjoys developing manual working methods so that they are consistent and algorithmic to such a degree that they become natural candidates for further automation, and so, in small increments, less truly becomes more.

Kim has worked as a lead consultant in numerous demanding BI and Data Platform projects during his career. He has trained over a hundred professionals.