Data and analytics languages should be prioritized far beyond graphical interface tools/software/services and should form a solid foundation of a skillset. Unlike software applications and various user interface controls which change frequently, the essential concepts and semantics of data languages such as SQL and DAX don’t change nearly as frequently and thus languages offer a much greater return on the time invested to learn them. For example, the fundamental PowerShell scripting knowledge I built up years ago using the Windows PowerShell ISE can still be applied today in many different tools, apps, and services that weren’t around back then such as Azure Function Apps and Visual Studio Code.
In almost every BI project I can remember, even projects that were explicitly intended to use low-code or no-code tools, it was the combination of different languages such as SQL, DAX, Kusto (KQL), Power Fx, and others that delivered the most value or which made the difference between project success and failure. Similarly, even in projects in which my role was intended to exclusively focus on the data model layer with DAX, I’ve almost always found myself also writing SQL, Power Query (M) and using other languages and code either in the data warehouse or on the reporting layer.
Brett has put a lot of thought into this and I think many of the principles apply outside of business intelligence work as well.