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This Tableau project demonstrates the power of Level of Detail (LOD) calculations through multiple real-world business scenarios — including customer analysis, sales performance tracking, and cohort analysis. It showcases how FIXED, INCLUDE, and EXCLUDE LODs can simplify complex analytical problems and deliver actionable insights.

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📊 Tableau Project – Level of Detail (LOD) Business Scenarios

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👀 What’s This Project About?

This Tableau project explores multiple real-world business use cases where Level of Detail (LOD) calculations help solve complex analytical challenges and uncover deeper insights across dimensions such as customers, products, and time.


🎯 Objective

The objective of this project is to showcase how Level of Detail (LOD) expressions in Tableau can be applied to solve real-world business problems such as customer analysis, sales performance tracking, and time-based comparisons. It focuses on helping analysts:

  • Understand and define what LOD expressions are and how they control aggregation levels in Tableau.
  • Apply FIXED, INCLUDE, and EXCLUDE calculations across different business scenarios.
  • Identify the dataset grain and explore how data granularity influences visualizations.
  • Analyze the impact of context and dimension filters on LOD results.
  • Troubleshoot common errors related to incorrect aggregation or unexpected outcomes.
  • Compare LOD calculations with Table Calculations to determine when each approach is most effective.

🧩 Business Scenarios Covered

1️⃣ Category Totals & % of Total

Use FIXED LOD to calculate the % of total sales by category, independent of visual filters.

2️⃣ Customer Order Frequency

Transform order count by customer into a dimension to analyze customer purchasing behavior.

3️⃣ Cohort Analysis

Group customers by acquisition quarter using FIXED LODs to measure retention and sales over time.

4️⃣ New vs Returning Customers

Compare how many customers are new versus returning across time periods.

5️⃣ Manipulation of Time Periods

Use LOD to calculate YoY growth or custom date comparisons.

6️⃣ Averages Using Additional Dimensions

Compute average sales by customer across region and category using INCLUDE LOD.

7️⃣ Comparative Analysis

Use EXCLUDE LOD to compare performance across categories, ignoring certain dimensions.


📁 Files

File Description
tableau-file.twbx Tableau workbook
Superstore.xlsx Dataset used for analysis
images/ Related Images

📸 Dashboard Previews

1️⃣ Dashboard 1

Performance

2️⃣ Dashboard 2

Performance


🌐 View Live Dashboard

🔗 Dashboard1 🔗 Dashboard2


🛠️ Tools & Techniques

  • Tableau Desktop / Tableau Public
  • Level of Detail (LOD) Calculations: FIXED, INCLUDE, EXCLUDE
  • Table Calculations
  • Data Modeling & Blending
  • Dashboard Design and Interactivity

👨‍💻 Author

Sujit Singh
Data Analyst | EXCEL | Tableau | Power BI | SQL | Python
📧 [sujit10x12@gmail.com]
🌐 [https://www.linkedin.com/in/sujit10x12/]


About

This Tableau project demonstrates the power of Level of Detail (LOD) calculations through multiple real-world business scenarios — including customer analysis, sales performance tracking, and cohort analysis. It showcases how FIXED, INCLUDE, and EXCLUDE LODs can simplify complex analytical problems and deliver actionable insights.

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