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Welcome & About this Wiki

Greetings! Welcome to this Wiki and Blog which is about Data & Analytics with Power BI from Microsoft.

My name is Jon and I am a project leader for business intelligence and analytics projects at DataVision in Zurich, Switzerland. My daily job is to design and implement business intelligence and analytics solutions with Microsoft Power BI for a broad portfolio of customers from various different industries. My job allowed me to gain a deep understanding of what works well and what not, how best practice for robust solution design looks like and how to make an analytics project a success. Having a Wiki or Blog was on my mind for a while and with this page I want to make it reality and share some of my knowledge.

If you would like to connect & chat, please find my LinkedIn profile here: LinkedIn Profile of Jon

Business Intelligence and Analytics with Microsoft Power BI [Full Book]

A hands-on implementation guide

When I started to write blog articles, I learned that this is something I really like doing. Blog articles though are individual pieces of knowledge and what is missing for me is a coherent structure that connects this knowledge. I therefore decided to write a book in September 2022 accordingly. The idea or goal of the book is to walk step-by-step through the implementation of a typical BI solution with Power BI.

The book contains a more generalized overview of the typical components of a BI solution. The larger part however uses an exemplary sales analysis use-case to demonstrate how to build a full solution with Power BI.

Book cover

Book cover (right-click and open in new tab for large version)

Buildings blocks of a business intelligence solution

Buildings blocks of a business intelligence solution (right-click and open in new tab for large version)

Blog articles

Besides the Wiki, I write blog articles in 6 different categories which follows the overall structure of developing and implementing a BI & analytics solution:

  1. Project Management
  2. Solution Design
  3. Data Transformation (ETL)
  4. Data Model
  5. Data Visualization & Reporting
  6. Publishing & Sharing