📊 Power BI - Map of Content
What is Power BI?
Power BI is Microsoft’s business intelligence platform for connecting to data sources, transforming data (Power Query/M), modeling relationships between tables, writing calculations (DAX), and building interactive reports/dashboards. It has three main layers: Power Query (get and shape data), the Data Model (relationships, DAX calculations), and Reports (visuals, formatting, interactivity).
graph LR A["Data Sources (Excel, SQL, Web, etc.)"] -->|Get Data| B["Power Query Editor (M language, transform/clean)"] B -->|Load| C["Data Model (relationships, DAX)"] C -->|Visualize| D["Report Canvas (charts, slicers, pages)"] D -->|Publish| E["Power BI Service (share, refresh, collaborate)"]
📂 Folder Contents
| # | Note | Covers |
|---|---|---|
| 01 | 01-Interface-Overview | Desktop UI: views, panes, ribbon |
| 02 | 02-Getting-Data-Connectors | Get Data, connectors, source settings, refresh |
| 03 | 03-Power-Query-Editor-M-Language | Query Editor, M language, transformations |
| 04 | 04-Data-Modeling-Relationships | Relationships, cardinality, cross-filter direction, star schema |
| 05 | 05-DAX-Fundamentals | DAX syntax, calculated columns vs measures, context |
| 06 | 06-DAX-Functions-Reference | Aggregation, logical, text, date/time functions |
| 07 | 07-DAX-Time-Intelligence-Context | CALCULATE, filter/row context, time intelligence |
| 08 | 08-Calculated-Columns-Tables-Measures | Calculated tables, measure organization, what-if parameters |
| 09 | 09-Visualizations-Chart-Types | Chart types, when to use each, custom visuals |
| 10 | 10-Filters-Slicers-Interactions | Filter pane, slicers, visual interactions |
| 11 | 11-Formatting-Themes-Conditional-Formatting | Formatting pane, themes, conditional formatting, tooltips |
| 12 | 12-Bookmarks-Buttons-Navigation | Bookmarks, buttons, drill actions, navigation |
| 13 | 13-Hierarchies-Groups-Drillthrough | Hierarchies, groups/bins, drillthrough pages |
| 14 | 14-Row-Level-Security | RLS roles, USERPRINCIPALNAME, dynamic security |
| 15 | 15-Publishing-Power-BI-Service | Workspaces, apps, gateways, scheduled refresh |
| 16 | 16-Performance-Optimization | Star schema, aggregations, DAX performance, Performance Analyzer |
| 17 | 17-Common-Errors-Gotchas | Common errors, circular dependencies, filter context traps |
🗺️ Conceptual Map
graph TD A[Power BI] --> B[Get & Transform] A --> C[Model] A --> D[Analyze] A --> E[Visualize] A --> F[Share] B --> B1[Connectors] B --> B2[Power Query / M] C --> C1[Relationships] C --> C2[Star Schema] C --> C3[Row Level Security] D --> D1[DAX Measures] D --> D2[Calculated Columns] D --> D3[Time Intelligence] E --> E1[Charts & Visuals] E --> E2[Slicers & Filters] E --> E3[Bookmarks & Navigation] F --> F1[Power BI Service] F --> F2[Scheduled Refresh] F --> F3[Apps & Workspaces]
⚡ Quick Reference - Core Workflow
1. Home > Get Data > choose a connector > load or Transform Data
2. In Power Query Editor: clean/shape data (remove columns, change types, merge queries)
3. Close & Apply > lands in the Data Model
4. Model view: draw relationships between tables
5. Report view: drag fields onto the canvas, pick a visual type
6. Write DAX measures for calculations (New Measure)
7. Add slicers/filters, format visuals, arrange the page
8. Publish to the Power BI Service, set up scheduled refresh
-- A typical first measure
Total Sales = SUM(Sales[Amount])
Sales YTD = TOTALYTD([Total Sales], 'Date'[Date])
Sales Growth % =
DIVIDE([Total Sales] - [Total Sales Last Year], [Total Sales Last Year])🔗 Related in LORE
- Excel Reference - Power Query and many DAX functions mirror Excel formulas/Power Pivot
- Pandas Reference -
groupby/pivot_tablemap conceptually to DAX measures + matrix visuals - PostgreSQL Reference - a common data source connector for Power BI
How to use this vault section
Same skeleton throughout: Definition -> Syntax -> Key Options -> Examples -> Notes/Gotchas. Use
Ctrl/Cmd+Oand type “PowerBI” or the note number to jump around.