📊 Round 5 — Tableau & Business Intelligence
Complete Guide From Scratch for Fresher Data Analyst
What to expect: 20–30 minutes testing your ability to build dashboards, choose the right visualizations, and understand Tableau-specific concepts. DecisionTree's core offering includes dashboards and visualization — this is a must-know skill.
1. What is Tableau?
Tableau is a drag-and-drop business intelligence tool that lets you create interactive charts and dashboards without writing code. It connects to databases, spreadsheets, and cloud sources.
| Component | Purpose |
|---|---|
| Tableau Desktop | Build charts and dashboards (your primary tool) |
| Tableau Server/Online | Publish and share dashboards with stakeholders |
| Tableau Prep | Clean and transform data before analysis (ETL) |
| Tableau Public | Free version — ideal for building a portfolio |
2. Measures vs Dimensions — The Most Fundamental Concept
| Concept | What It Is | Example | In Tableau |
|---|---|---|---|
| Dimensions | Categorical fields — answer "WHAT" or "WHO" | City, Product Name, Segment | 🔵 Blue pills — create headers and groups |
| Measures | Numerical fields — answer "HOW MUCH" | Revenue, Profit, Quantity | 🟢 Green pills — get aggregated (SUM, AVG) |
🧠 Aise yaad rakho: Exam mein "Subject" = Dimension, "Marks" = Measure. X-axis pe Dimension, Y-axis pe Measure — bar chart ban gayi.
Continuous vs Discrete
| Type | Meaning | Color | Example |
|---|---|---|---|
| Discrete | Separate, distinct values — creates headers | 🔵 Blue | City names, Product categories, Months as labels |
| Continuous | A flowing range — creates an axis | 🟢 Green | Exact dates, Revenue amounts, Temperature |
🧠 Interview trick: "What happens when you change Date from Continuous to Discrete?" — Line chart becomes a bar chart. Mention this to impress.
Data Types in Tableau
| Type | Symbol | Example |
|---|---|---|
| String | Abc | Customer names, product names |
| Number (Integer) | # | Quantity, count of orders |
| Number (Decimal) | #.# | Revenue, profit margin |
| Date | 📅 | Order date, signup date |
| Date & Time | 📅⏰ | Transaction timestamp |
| Boolean | T/F | Is_Active, Has_Subscription |
| Geographic | 🌍 | City, State, ZIP code (auto-detected) |
3. Chart Types — When to Use What
| What You Want to Show | Chart Type | Example |
|---|---|---|
| Compare categories | Bar Chart | Revenue by city |
| Trend over time | Line Chart | Monthly sales over 12 months |
| Part of a whole | Pie/Donut Chart | Market share by brand (use only for ≤5 categories) |
| Distribution | Histogram | Age distribution of customers |
| Relationship between 2 variables | Scatter Plot | Ad spend vs Sales |
| Geographic data | Map | Sales by state/city |
| Hierarchical categories | Treemap | Category → Sub-category sized by revenue |
| Performance vs Target | Bullet Chart | Actual vs Target sales by region |
| Outliers and spread | Box Plot | Salary distribution by department |
| Feature correlations | Heatmap | Correlation between numerical features |
| Ranking changes over time | Bump Chart | How product rankings shift monthly |
| Flow/funnel | Funnel Chart | Conversion funnel: Visit → Cart → Purchase |
🧠 Common mistake: Pie chart mein 10 categories daal dena — unreadable. Rule: Pie chart sirf tab jab categories ≤ 5.