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Power BI Reports – Data Analysis & Insights

This repository contains Power BI reports designed to analyze, visualize, and present insights from different datasets. The goal is to provide clean and interactive dashboards that help in decision-making using data-driven approaches.


Features

  • Interactive dashboards with filters and slicers
  • Visualizations for trend analysis, KPIs, and drill-throughs
  • Reports built with Power BI Desktop
  • Example datasets for testing and practice

Repository Structure

Sales Performance talks about the Sales Performance in Retail-Sales Dataset

  • Top Sales by Quality
  • Product Category by Highest Revenue
  • Total Revenue over a period of time
  • Measures : Total Revenue, Quarterly Revenue and Yearly Revenue

Sales Performance


Customer Behavior tells about the behavior of the Customers by Gender and Age Categories

  • Total Revenue by Age Group
  • Average Age of Customers per Category
  • Average Transactions per Customers
  • Measures : Unique Customers, Total Revenue, Total Transactions and Average Revenue

Customer Behavior


Product Analysis, Segmentation and Targetting has an analysed visualizes of products, it segments the product based on Category, Gender and Age Group. The Targetting targets on the specific insights to increase profit(sales).

  • Highest Average Unit Price by Product category
  • Product Category based on Quantity Sold
  • Most Expensive Purchase by Age and Gender
  • Average Transaction by customer
  • Product category Preference by Gender

Product Analysis, Segmentation   Targeting


DAX Queries

Total Revenue

Total Revenue = SUM('retail_sales_dataset'[Revenue])

Quarterly Revenue

Total Revenue Quarterly = CALCULATE([Total Revenue],DATESINPERIOD('retail_sales_dataset'[Date],MAX('retail_sales_dataset'[Date]),-1,QUARTER))

Yearly Revenue

Total Revenue Yearly = CALCULATE([Total Revenue],DATESINPERIOD('retail_sales_dataset'[Date],MAX('retail_sales_dataset'[Date]),-1,YEAR))

Total Transaction

Total Transactions = DISTINCTCOUNT('retail_sales_dataset'[Transaction ID])

Average Revenue per Gender

Total Revenue average per Gender = 
AVERAGEX(
	KEEPFILTERS(VALUES('retail_sales_dataset'[Gender])),
	CALCULATE([Total Revenue])
)

Average Revenue

Average Revenue = AVERAGE('retail_sales_dataset'[Revenue])

Power Point - Background

I created the background for this Visualization using MS PowerPoint 1 2


How to use

  • Import the retail_sales_dataset into Power BI.
  • Add these DAX queries in the Modeling → New Measure section.
  • Use them in cards, visuals, and dashboards to monitor revenue trends.
  • Add Background, Go styling your Canvas !

Tools used

  • Power BI
  • Power Point
  • DAX Queries

Author

K N Dinesh Kumar dineshdhieraj02@gmail.com

About

This repository contains Power BI reports designed to analyze, visualize, and present insights from different datasets. The goal is to provide clean and interactive dashboards that help in decision-making using data-driven approaches.

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