Author Description

DAX is the language of data analysis in Microsoft Power BI, Azure Analysis Services, and Excel Power Pivot. DAX is a powerful language that can quickly empower you to analyze year-over-year or rolling 12 months calculations. It is rare to find an analytics solution using Microsoft technologies (especially Power BI) that doesn't require some calculations to be written by DAX. As a Power BI (or Microsoft BI) developer, it is essential to learn this language and master it. Learning a language is not just learning the structure and functions. It is learning how, where, and when to use it so that you can solve real-world problems with it. In my training and consulting experience on Power BI, I realized that DAX is the weak point for many Power BI users. DAX itself is not a complex language. It is merely a language of expression. The complexity of learning DAX is not the formula or the functions. It is how to use it in real-world scenarios and how it performs on a dataset or visual. I have been writing many blogs about DAX for many years. My blog articles are all coming from my experience working with Power BI. I found it helpful to compile them all in a book. Because my blog articles practically explain things, I thought it better to title it as a practical way of learning DAX by examples. Indeed, there are books, articles, and Microsoft documentation on how each function works where and how. However, learning these through an example would bring a new way of understanding it. A good analytics solution is a combined outcome of a good data model, good data preparation, and good analytics and calculations. I have written another book about the Basics of modeling in Power BI. This book is covering the calculation and DAX aspects of it. This book is for you if you are building a Power BI solution. Even if you are just visualizing the data, calculations are an essential part of analytics. You do need to have the calculation ready before visualizing it. Th