Data Analytics - Lego Sets Analysis

1: Transform the data using Power Querry such as removing unnecessary columns, remaning columns, removing duplicate columns.

2: Create conditional columns like for Age Range (“Over 18”, “10 to 17”, “5 to 9”, “1 to 4”) and Price Range (>$500 = “$$$$$”, >$100 = “$$$$”, >$50 = “$$$”, >$25 = “$$”, otherwise “$”)

3: DAX Calculations

4: Placeholders

5: Insert a table to show name, set_id, theme, Age Range, Avg. Pieces, Avg. Price and Price Range

6: Thumbnails

7: Page Navigation

8: Edit visual interactions to prevent table selections from filtering the top-level cards

9: Create a numeric range parameter (Max Price) ranging from 0-850 and incrementing by 5. Add a slicer to the page, and a measure that allows you to filter the table based on the maximum price selected

10: Use bookmarks and button actions to allow users to reset all filters on the page (BONUS: customize the format for “on hover” and “on press” states)

11: Create a new report page with a decomposition tree visual to analyze Total Sets by category, theme group, theme and name, and add buttons to navigate between pages