BI Tools & Visualization
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# BI Tools & Visualization ## 🎯 Learning Objectives - Compare BI tools (Tableau, Power BI, Looker) - Design effective dashboards for decision-making - Connect BI tools to data sources - Understand self-service BI vs managed BI ## 📖 Core Content ### 7.1 BI Tool Comparison Feature Tableau Power BI Looker Vendor Sale...
BI Tools & Visualization
🎯 Learning Objectives
- Compare BI tools (Tableau, Power BI, Looker)
- Design effective dashboards for decision-making
- Connect BI tools to data sources
- Understand self-service BI vs managed BI
📖 Core Content
7.1 BI Tool Comparison
| Feature | Tableau | Power BI | Looker |
|---|---|---|---|
| Vendor | Salesforce | Microsoft | |
| Deployment | Desktop + Server | Desktop + Service | Cloud-native |
| Pricing | $$ $ | $$ | $$$ |
| Data sources | 60+ | 100+ | 50+ |
| AI features | Explain Data | Q&A, AI visuals | Looker ML |
| Best for | Visual analytics | Microsoft ecosystem | Embedded analytics |
7.2 Dashboard Design Principles
- KPI hierarchy: Most important metric top-left
- Context: Always show trends, not just current values
- Interactivity: Enable drill-down and filtering
- Simplicity: One dashboard = one topic = one question answered
- Consistency: Same color scheme, font, layout throughout
- Performance: Minimize data load, use extracts/cubes
7.3 Self-Service BI Architecture
(Diagram)
The semantic layer translates technical table names into business-friendly terms (e.g., "dim_customer" → "Customer Name"). This enables self-service: business users can create their own reports without SQL knowledge.
📝 Practice Questions
Q1: Power BI vs Tableau — which to choose?Choose Power BI if: (1) already in Microsoft ecosystem (Excel, Azure, Office 365), (2) cost-sensitive (70/user), (3) need tight Excel integration. Choose Tableau if: (1) need advanced visual analytics, (2) complex calculations and parameters, (3) large enterprise with dedicated BI team. Tableau is more powerful but more expensive. Q2: What is a semantic layer in BI?A semantic layer sits between data sources and BI tools. It translates database schemas into business-friendly terms and provides pre-built measures and dimensions. Benefits: (1) business users don't need SQL, (2) consistent metrics across the organization, (3) centralized business logic. Q3: Why is dashboard performance important?Slow dashboards lose user trust. If a dashboard takes 30 seconds to load, executives won't use it. Solutions: (1) use data extracts/aggregates instead of live queries, (2) pre-aggregate at the database level, (3) limit dashboard to essential metrics, (4) schedule data refreshes during off-hours. Join Discord PreviousData GovernanceNextData Warehouse Design