Super-Store-Sample-Data-Analysis

This Tableau Data Analysis project revolves around exploring the Superstore Sample dataset. The objective is to derive meaningful insights and create impactful visualizations to aid decision-making. Below is a brief summary of the project's key components and outcomes.

You can view my interactive Tableau Dashboard here.

Implementation Highlights:

Data Preparation:

• Import Superstore Sample dataset into Tableau.
• Conduct data cleaning and transformation for improved analysis.

Key Reports and Dashboards:

Sales and Profit by Customer Report:

• Visualize sales and profit by customer segments.

• Incorporate filters for focused analysis.

  

Sales Forecast Report:

• Apply forecasting techniques for predicting future sales.
• Compare forecasted values with actual sales.

Product Dashboard:

Display sales by product category, profit by product name, and sales by region and state.

Waterfall Chart for Sales and Subcategory:

Illustrate incremental contributions to sales and profit from subcategories.

Lollipop Chart for Category and Sales:

Enhance the understanding of the relationship between categories and sales.

Comparison of Three Categories:

Analyze and compare the performance of three selected product categories.

Overview Dashboard:

Showcase monthly sales trends, customer counts by region, profit ratios, and detailed order information.

Story for previous Points:

Craft a compelling narrative highlighting insights derived from the product dashboard and waterfall chart.

Conclusion:

This documentation serves as a guide through the entire process, offering transparency into data preparation, report creation, and the storytelling aspect of the Tableau Data Analysis project. For a detailed exploration, refer to the full documentation.