Overview
This lecture provides a comprehensive introduction to Power BI, including its core concepts, architecture, main features, practical report/dashboard building, comparison with Tableau, and essential interview questions.
Introduction to Power BI & Business Intelligence (BI)
- Business Intelligence (BI) transforms raw data into useful information for decision-making.
- BI evolved through three waves: IT-dependent, analyst self-service, and end-user empowerment.
- Data visualization is crucial for simplifying complex data and identifying patterns.
- Power BI is Microsoft's BI tool for creating visualizations and interactive dashboards.
Power BI Core Features and Architecture
- Power BI enables real-time trend spotting, hidden insights, advanced analytics, and secure enterprise connectivity.
- Main components: Power Query (data access/transform), Power Pivot (data modeling), Power View (visualization), Power Map (geographic/time-based data), Power BI Services (cloud), Q&A (natural language queries), Data Gateway, and Data Catalog.
- Power BI architecture: Data Integration (from various sources), Data Processing (cleaning/transformation), Data Presentation (visualization/dashboard).
Building Blocks of Power BI
- Visualization: Graphs, charts, maps to display data insights.
- Dataset: Collection of data from various sources.
- Report: Multi-page collection of visualizations.
- Dashboard: Single-page summary of key visuals (tiles).
- Tile: Individual visual element pinned to a dashboard.
Power BI Desktop: Installation & Basic Usage
- Install Power BI Desktop from the official website.
- Import data from Excel, databases, web, and other sources.
- Visualizations are created by dragging fields onto the canvas.
- Reports are saved as .pbix files and can be published to the Power BI Service for sharing.
Visualizations & Dashboard Creation
- Various charts available: bar, column, line, area, pie, donut, tree maps, maps, funnel charts, slicers, gauges, cards, KPI visuals, tables, and matrices.
- Pin visuals to dashboards to create interactive stories.
- Dashboards are for summary views; reports allow deeper, multi-page analysis.
- Real-time and interactive features like natural language queries (Q&A) are supported.
KPI Indicators in Power BI
- KPI (Key Performance Indicator): Visual cue showing progress toward business goals.
- Requires actual value, target value, and optional threshold.
- KPI visuals can be formatted, color-coded, and customized for various scenarios.
Comparison: Power BI vs Tableau
- Power BI excels in custom visuals, integration, and cost; Tableau is strong in pure data visualization and scalability.
- Power BI is easier for beginners; Tableau suits more curated, advanced visualization needs.
Power BI Interview Questions (Key Concepts)
- Self-Service BI: Lets end-users build their own reports/visuals.
- Components: Power Query, Power Pivot, Power View, Power Map, Data Gateway, Q&A, Service.
- Core processes: ETL (Extract, Transform, Load), data modeling, DAX (Data Analysis Expressions) for calculations, row-level security.
- Data sources: Excel, databases, web, cloud services, APIs.
- Filters: Visual, page, report, and drill-through filters.
- Measures vs calculated columns: Measures are dynamic, columns are stored in the model.
- Security: Managed via user roles and row-level security.
Key Terms & Definitions
- Business Intelligence (BI) — Tools/techniques converting raw data into actionable insights.
- Power BI — Microsoft’s BI tool for analytics and visualization.
- Dataset — Collection of data used for analysis.
- Report — Multi-page compilation of visualizations.
- Dashboard — Single-page summary of key visuals.
- DAX — Data Analysis Expressions, Power BI’s formula language.
- Power Query — ETL component for data prep.
- Power Pivot — In-memory data modeling engine.
- KPI — Key Performance Indicator, tracks progress toward goals.
- Natural Language Query — Asking data questions in everyday language.
Action Items / Next Steps
- Practice building reports and dashboards in Power BI Desktop.
- Review main Power BI components and their purposes.
- Explore sample datasets and try different visualization types.
- Prepare for interviews by practicing DAX, data modeling, and security setup.
- Optional: Compare Power BI and Tableau on your own datasets.