So, in no particular order:
Power Query is the underlying foundation to get, clean, and transform data (sometimes called extract, transform, load, or ETL)
What is Power Query?
Power Pivot and
Power BI are two tools that use Power Query. Power Pivot is part of excel, and Power BI is a separate program that also uses Power Query, but with a much higher emphasis on the visualization side. The visual types and customization is far superior to what you can achieve in excel.
Power View is (I believe) an unsupported and trimmed down version of Power BI. Don't use this. Use Power BI Instead.
Power View - Overview and Learning
To deliver a compelling experience for visual data exploration in a focused tool, we are shifting all investment to Power BI Desktop for this workload, and have concluded new feature development for Power View. Power BI Desktop is now the recommended tool for visual data exploration and reporting, and Excel continues to be the broad tool for deep analytics. The Power BI Service allows for simple publishing of dashboards for both Power BI reports and Excel workbooks, and also enables users to analyze Power BI data in Excel. Each of these tools is optimized for the different needs of business analysts, and together, the suite is deliberately designed to work together.
Power Map is simply a visualization tool for data in excel. Once you have your data set up, it's just a more advanced way to show your data on a map.
Get started with Power Map
DAX and
M are two different languages used to help in data transformation:
Power BI: M vs. DAX and Measures vs. Calculated Columns. M code is the underlying foundation of Power Query (i.e. when you press buttons in Power Query you are creating M). DAX is also used in both Power BI and Power Pivot.
Overall, the rough process is to use Power Query to load and transform data (thus creating your queries in M code behind the scenes), apply any additional logic with DAX formulas (if any - for basic analysis this is often not needed), and then use whichever tool is more appropriate (Power Pivot or Power BI) to visualize the results of your analysis.
