Online D♯ Intro Course

Description

In the 4-hour on-line and public D♯ intro training course you will learn how to build and maintain a low-code Data Warehouse using the D♯ Toolbox. Learn the modeling, mapping and parametrization needed to automatically convert a conceptual model into Data Vault 2.0 tables and load procedures that populate them. We will meet in the Microsoft Teams online classroom, and everybody will have a personal training environment in Azure Lab Services.

Who should attend?

Technical architects, developers and anyone interested in what is needed to build automated, modern low-code DW solutions.

Content

  • D♯ methodology overview (including DataVault 2.0 basics)
  • Modeling
    • Tool overview (Visual Paradigm, Ellie)
    • Modeling details
  • SmartEngine overview
  • Hands-on tutorials: Building and Maintaining the Raw Vault

Details

  • English and Finnish (course materials are in English)
  • The virtual class room in Teams and Microsoft Azure Labs allows six participants.
  • During the training session, you will complete the first three tutorials, that demonstrate how to create and iteratively change the example data warehouse.
  • After the course you have the opportunity to continue the learning process by completing the additional seven tutorials embedded in the toolbox. By completing all your tutorials, you are on your way to D♯ Certification.
  • 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.

Preparations

  • 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.