We will introduce SQL clauses and syntax first followed by their DAX equivalent. We will look at how the SQL clauses in the Logical SQL query processing steps below translated into DAX as a functional language. We are going to make the initial learning process simple and straight forward by comparing SQL and DAX queries. We will do this by simply translating SQL queries to DAX queries. We will learn how the pre-built relationship between tables in a Tabular Model affects DAX language as opposed to using join statements in SQL simply because tables in SQL Server databases are not joined to each other. In Part II we are going to continuing to learn DAX by solidifying our understanding of its functional nature compared to the declarative nature of SQL. If you have not done so yet, please refer to Part I, especially for the concept outlined in bullet points 3 and 4, they form the foundation of this learning process. Knowing and always keeping this last point in mind and also understanding how functional language syntax is constructed makes transitioning from SQL to DAX a lot easier. Finally, we learned that, even though both DAX and SQL languages can achieve the same query results, SQL is a Declarative Language whilst DAX is a Purely Functional Language.It will help one to grasp the effects of DAX relationships, filter propagation, interactivity and their effects on the DAX formulas and expression that you will write. Understanding the Extended Tables and other Tabular Models concept is key.Because tables are left joined to other tables on the many-to-one side, tables in Tabular Models are essentially Extended Tables.In both databases the basic elements are tables, but in a SQL Server Database, tables are isolated units whilst in Tabular Models, tables are all joined into one physical data model.We examined the key similarities and differences between and a SQL Server Database and the Tabular Model that power T-SQL and DAX respectively.Interactive visualization tools take the concept of data visualization a step further by using data modeling and technology to enable end-user to drill down into visuals to fully explore and analyze data. We also learned the benefits of interactive visualization that comes with tools like Power BI.There are many books available that teach this art and science of analytical storytelling. We learned that applying these can increase one's potential to effectively communicate decision making insights to drive action. First, we discussed the importance of learning and applying Data Visualization techniques.In Part I of the series, we discussed some very important Data Visualization and Tabular Model concepts that are essential to the DAX learning process, esp. This is useful for developers starting to learn the DAX language to more advanced developers who have struggled to adjust to the language coming from a SQL background. In response to my approach in the popular MDX Guide for SQL Folks series, I am using SQL as a good frame of reference for starting or developing a new approach for improving your Data Analysis Expression(DAX) language learning experience.
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