https://github.com/tushard48/analyzing-usa-market-trends-a-financial-overview

In-depth analysis of US market trends, encompassing economic indicators, industry performance, and financial data
https://github.com/tushard48/analyzing-usa-market-trends-a-financial-overview

data data-visualization powerbi

Last synced: 11 days ago
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In-depth analysis of US market trends, encompassing economic indicators, industry performance, and financial data

• Host: GitHub
• URL: https://github.com/tushard48/analyzing-usa-market-trends-a-financial-overview
• Owner: TusharD48
• Created: 2024-08-01T12:13:42.000Z (5 months ago)
• Default Branch: main
• Last Pushed: 2024-08-01T12:36:03.000Z (5 months ago)
• Last Synced: 2024-11-08T11:43:07.374Z (2 months ago)
• Topics: data, data-visualization, powerbi
• Homepage:
• Size: 212 KB
• Stars: 1
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
## Analyzing-USA-Market-Trends-A-Financial-Overview

### Project Overview

This Power BI project aims to provide a comprehensive analysis of the USA market, focusing on key financial trends and indicators. By leveraging data-driven insights, this project enables stakeholders to understand market dynamics, identify opportunities, and make informed decisions.

### Description:

This dataset contains sales information for various products across different countries, segments, and channels. It includes details such as:

- Segment: Customer segment (Government, Midmarket, Enterprise, Small Business, Channel Partners)

- Country: Country where the sale occurred

Product: Product sold

- Discount Band: Discount applied to the product

- Units Sold: Number of units sold

- Manufacturing Sale Price: Unit price before discounts

- Gross Sales: Total sales revenue before discounts

- Discounts: Total discount amount

- COGS Profit: Cost of Goods Sold Profit

- Date: Sale date

- Month Name: Month of the sale

- Year: Year of the sale

## Data Dictionary:

- Segment: Categorical variable representing the customer segment.

- Country: Categorical variable representing the country where the sale occurred.

- Product: Categorical variable representing the product sold.

- Discount Band: Categorical variable representing the discount applied to the product.

- Units Sold: Numerical variable representing the number of units sold.

- Manufacturing Sale Price: Numerical variable representing the unit price before discounts.

- Gross Sales: Numerical variable representing the total sales revenue before discounts.

- Discounts: Numerical variable representing the total discount amount.

- COGS Profit: Numerical variable representing the Cost of Goods Sold Profit.

- Date: Date variable representing the sale date.

- Month Name: Categorical variable representing the month of the sale.

- Year: Numerical variable representing the year of the sale.

## Data Cleaning and Preprocessing:

[ data cleaning or preprocessing steps performed, such as handling missing values, outliers, or data inconsistencies.]

## Potential Analysis:

- Sales performance by segment, country, and product

- Impact of discounts on sales revenue

- Product profitability analysis

- Customer segmentation and targeting

- Sales trend analysis over time

## Data Usage:

This dataset can be used for various analytical purposes, including sales forecasting, market analysis, customer behavior analysis, and pricing optimization.

## Example of basic visualisation