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Sales Insights Data Analysis Project

Overview:
This project uses Power BI and SQL to analyze sales data, helping the company gain insights into sales trends, identify top-performing products, and target high-value customers. The goal is to make informed business decisions that could drive an estimated revenue increase of 7% in the next quarter.

Power BI Dashboard

A Power BI dashboard was created to visualize key metrics like:

• Total Revenue
• Sales Quantity by Markets
• Revenue Trends Over Time
• Top Customers and Products

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Table of Contents

• Project Phases
• Technologies Used
• Key Highlights
• SQL Analysis
• Power BI Analysis
• Conclusion

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Project Phases

1. Requirement Gathering - Identifying business needs and relevant sales metrics.
2. Data Collection - Extracting sales data from company databases.
3. Data Processing - Cleaning and structuring data for analysis.
4. Data Modeling - Building models to facilitate Power BI visualizations.
5. Dashboard Building - Designing an interactive dashboard.
6. Deployment - Publishing the dashboard for stakeholders.

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Technologies Used

• SQL: For data extraction, transformation, and analysis.
• Power BI: For creating interactive and insightful data visualizations.

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Key Highlights

• Developed a Power BI dashboard that provides insights into sales trends and patterns.
• Enabled stakeholders to track performance and make data-driven decisions.
• Identified actionable insights that can potentially increase revenue by 7%.

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SQL Analysis

Here are some key SQL queries used in the analysis:

• Show all customer records

  SELECT * FROM customers;

• Show total number of customers

  SELECT COUNT(*) FROM customers;

• Retrieve transactions for the Chennai market

  SELECT * FROM transactions WHERE market_code = 'Mark001';

• Show total revenue in the year 2020

  SELECT SUM(transactions.sales_amount) 
  FROM transactions 
  INNER JOIN date ON transactions.order_date = date.date 
  WHERE date.year = 2020 
    AND (transactions.currency = 'INR' OR transactions.currency = 'USD');

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Power BI Analysis

• Currency Normalization Formula
  To handle multiple currencies, the norm_amount column was created in Power BI to standardize revenue using the formula below:

  = Table.AddColumn(#"Filtered Rows", "norm_amount", each if [currency] = "USD" or [currency] = "USD#(cr)" then [sales_amount] * 75 else [sales_amount], type any)
  

  This formula assumes an exchange rate of 1 USD = 75 INR.

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Conclusion

This project demonstrates the value of data analysis and visualization in making informed business decisions. By analyzing sales data, the dashboard provides insights that could help increase revenue by approximately 7% next quarter. Future improvements could include:

• Real-time data integration for up-to-date insights.
• Predictive analytics for forecasting future sales trends.

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Connect with me on LinkedIn if you'd like to discuss this project or explore more about my work in data analysis.

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