Introduction to Power BI

Power BI is a business analytics tool by Microsoft used to visualize data and share insights across your organization.

It combines data preparation, modeling, and visualization into a single workflow, enabling self‑service BI and scalable enterprise reporting.

Power BI Basics

Power BI Desktop

Install and create reports locally. Load datasets, transform data, and build semantic models.

Power BI Service

Cloud-based platform for publishing, sharing, scheduling refresh, and collaboration.

Power BI Mobile

Access reports and dashboards with optimized mobile layouts.

Data Import & Transformation

Connecting Data

• Excel
• CSV
• SQL Server
• SharePoint / Web

Data Cleaning (Power Query)

Remove duplicates, filter rows, replace values, split/merge columns, and create reusable query steps.

Example: Filter sales > 1000, Replace null with 0
      

Data Modeling

Create relationships between tables, define keys, and use star schemas for clear filter flow and better performance.

DAX (Data Analysis Expressions)

DAX is used for calculations, measures, and complex aggregations. It relies on filter context and row context to evaluate results, and CALCULATE can modify filter context dynamically.

SUM(Sales[Amount])
AVERAGE(Sales[Amount])
CALCULATE(SUM(Sales[Amount]), Sales[Region]="East")
FILTER(Sales, Sales[Amount]>1000)
      

Best practices:

• Prefer measures over calculated columns for performance and flexibility
• Use variables (VAR) to simplify complex logic
• Use time intelligence functions for period comparisons

Sales YTD :=
CALCULATE([Total Sales], DATESYTD('Date'[Date]))

Sales LY :=
CALCULATE([Total Sales], SAMEPERIODLASTYEAR('Date'[Date]))
      

Advanced DAX Examples

// Remove all filters except Region
Sales by Region :=
CALCULATE([Total Sales], ALLEXCEPT(Sales, Sales[Region]))

// Top 5 products by sales
Top5 Sales :=
CALCULATE([Total Sales], TOPN(5, VALUES(Product[ProductName]), [Total Sales], DESC))

// Rank products by sales
Product Rank :=
RANKX(ALL(Product[ProductName]), [Total Sales], , DESC)
      

Use measures for dynamic calculations and avoid heavy calculated columns unless required for relationships.

Data Visualizations

• Bar / Column Charts
• Line Charts
• Pie / Donut Charts
• Maps & Filled Maps
• Tables & Matrices
• Cards & KPIs

Example:

Drag “Sales Amount” to Values, “Region” to Axis → Select Clustered Column Chart

Best practice: keep visuals focused, use consistent color palettes, and highlight key insights with labels or tooltips.

Advanced Power BI

Advanced Power BI focuses on scalable modeling, optimized DAX, and governance for enterprise reporting.

Calculated Columns & Measures

Profit = Sales[Revenue] - Sales[Cost]
Total Sales = SUM(Sales[Amount])
      

Advanced Visuals

Custom visuals from marketplace, conditional formatting, bookmarks, slicers, and drill-through reports.

Use tooltips and report page drillthrough to provide context without cluttering dashboards.

Row-Level Security (RLS)

Restrict data access for specific users based on roles and DAX filters. Combine static roles with dynamic security from user tables.

Power BI Dashboard

Combine multiple reports, pin visuals, and share dashboards with refresh schedules and permissions.

For performance, optimize data models with star schemas, avoid bi‑directional filters, and limit high‑cardinality columns.

Deployment Pipelines & Incremental Refresh

Use deployment pipelines to promote content from dev to test to production with governance. Incremental refresh keeps large datasets fast by only updating new partitions.