This project aims to analyze and visualize the sales data for Retail and Food Services in the U.S.A. The data is sourced from the U.S. government website and has been processed using SQL to create a database for easy management and analysis. The main focus of this project is to explore the sales data based on NAICS (North American Industry Classification System) code and category.
├── LICENSE
├── README.md <- README .
├── query <- Code of the DB creation and queries.
│ │
│ └── retail_sales_tables_db.sql <- DB creation.
│ └── analysis.sql <- Final queries.
│ └── query_data <- Final queries data.
├── reports <- Folder containing the final reports/results of this project.
│ │
│ └── query_report.docx <- Final analysis report Document.
│ └── query_report.pdf <- Final query report in PDF for verifying data.
│
├── src <- Source for this project.
│
├── data <- Datasets used and collected for this project.
The dataset used in this project contains historical sales data for Retail and Food Services in the U.S.A. The data has been collected from the U.S. government website, which ensures its authenticity and reliability. The dataset includes information such as NAICS code, category, sales figures, geographical regions, and time period (e.g., monthly or yearly).
To facilitate data management and analysis, a SQL database has been created to store the dataset. SQL provides a robust and efficient way to query and manipulate the data. The database schema has been designed to ensure proper organization and ease of use. The structure of the database enables seamless integration with various data visualization tools.
The data obtained from the U.S. government website might require some preprocessing to clean and transform it into a suitable format for analysis. SQL queries have been utilized to clean, filter, and transform the data as necessary. This ensures that the data used for the dashboard is accurate and reliable.
Overview: A summary of key performance indicators, such as total sales, top-performing categories, and regional distribution of sales.
Sales by NAICS Code: Visual representations of sales figures for various NAICS codes, allowing users to identify the most significant contributors to overall sales.
Sales by Category: Graphs and charts illustrating sales for different categories within Retail and Food Services.
Geographical Analysis: Maps and charts showing sales distribution across different regions of the U.S.A.
Time Series Analysis: Trends and seasonal patterns in sales data, helping users to identify patterns over time.
Filtering and Interactivity: Interactive elements allowing users to filter data based on specific criteria and perform ad-hoc analysis.
SQL: For data extraction, transformation, and loading into the database.
Database Management System: PostgreSQL to host and manage the dataset.
Programming Languages: SQL for data processing and scripting.
Conclusion The Sales for Retail and Food Services in U.S.A. project provides a comprehensive analysis of sales data within the Retail and Food Services sectors. The use of SQL and data from the U.S. government website ensures data accuracy and reliability. The interactive dashboard offers a user-friendly interface to explore the data visually and gain valuable insights. This project is valuable for businesses, policymakers, and researchers looking to understand and leverage sales trends in the U.S.A.
- ©2023 Tushar Aggarwal. All rights reserved
- Medium
- Tushar-Aggarwal.com
- New Kaggle
If you have any questions, suggestions, or just want to say hello, you can reach out to us at Tushar Aggarwal. We would love to hear from you!