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Sql Ecommerce Analysis Task3 Readme Md At Main Github

Leo Migdal
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sql ecommerce analysis task3 readme md at main github

There was an error while loading. Please reload this page. This project contains SQL queries written for performing data analysis on an Ecommerce dataset. The database was created using SQLiteOnline, and CSV files were imported to form the following tables: Due to the import method, the columns were assigned generic names (c1, c2, c3…), so all queries use these column names. 📌 Tasks Completed ✔ 1.

SELECT, WHERE, ORDER BY Basic filtering and sorting of users. ✔ 2. GROUP BY + Aggregations Counting users by country. ✔ 4. SUBQUERY Identify products ordered more than once. There was an error while loading.

Please reload this page. SQL-Based Ecommerce Analytics This project contains a complete Ecommerce SQL database with tables for customers, products, orders, and order items. The database was created, populated with sample data, and analyzed using multiple SQL queries. Key tasks include performing JOINs, aggregations, subqueries, monthly revenue analysis, identifying top-spending customers, best-selling products, and category-based purchases. 📘 Task 3 — SQL for Data Analysis Data Analyst Internship | Elevate Labs Tool Used: DB Browser for SQLite Dataset: Custom E-commerce SQL Database (created manually) 📝 Overview This task focuses on applying SQL techniques to extract, analyze, and understand structured data stored in an E-commerce database.

Using SQLite, the database was created from scratch and includes customers, products, orders, and order item transactions. The goal is to practice real-world data analysis operations such as filtering, sorting, joining tables, aggregating values, using subqueries, creating views, and optimizing queries using indexes. 📂 Repository Structure Day 3 – Task 3 │── README.md │── sample.db (Ecommerce_SQL_Database - SQLite database file) │── sample.sql (All queries + table creation + data) └── Sql Queries Screenshots.pdf (Query outputs) 🗃️ E-commerce Database Schema Tables Included: • customers — Customer details • products — Product information • orders — Customer orders • order_items — Items purchased in each order The database contains sample data... 🧪 SQL Concepts Covered This project includes full coverage of: ✔ SELECT statements ✔ WHERE filters ✔ ORDER BY sorting ✔ GROUP BY aggregations ✔ Aggregate functions (SUM, AVG, COUNT, MAX, MIN) ✔ JOINS... This repository contains my complete solution for Task 3 of the Data Analyst Internship assignment.

The goal of this task was to perform SQL-based data analysis on an E-commerce relational database using MySQL Workbench. To analyze an E-commerce database using SQL by applying: This task demonstrates real-world SQL data analysis skills. The project uses an E-commerce dataset consisting of four relational tables: Order-level information including user ID and status. This project fulfills Task 3: SQL for Data Analysis .

It delivers a reusable e-commerce dataset plus end-to-end analytical SQL that demonstrates filtering, joins (inner/left/right), subqueries, aggregates, views, window functions, and indexing. Right JOIN note: SQLite lacks RIGHT JOIN. The script includes the ANSI query for engines that support it; if you stay on SQLite, simply swap table order and use LEFT JOIN. Capture console screenshots for every required query, package them with this repository, and submit per internship instructions. Chinook SQLite database (renamed to ecommerce.db) There was an error while loading.

Please reload this page. End-to-end SQL data analysis project featuring schema creation, data modeling, aggregate queries, joins, subqueries, views, and performance optimization. Fully executed using SQLite with screenshots and documentation. 📌 Overview This project demonstrates SQL skills for data analysis using an E-commerce dataset. The tasks include:

Using joins, subqueries, GROUP BY, views, and indexes Query optimization using EXPLAIN QUERY PLAN All queries were executed using SQLite (DB Browser for SQLite).

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There Was An Error While Loading. Please Reload This Page.

There was an error while loading. Please reload this page. This project contains SQL queries written for performing data analysis on an Ecommerce dataset. The database was created using SQLiteOnline, and CSV files were imported to form the following tables: Due to the import method, the columns were assigned generic names (c1, c2, c3…), so all queries use these column names. 📌 Tasks Completed ✔ 1...

SELECT, WHERE, ORDER BY Basic Filtering And Sorting Of Users.

SELECT, WHERE, ORDER BY Basic filtering and sorting of users. ✔ 2. GROUP BY + Aggregations Counting users by country. ✔ 4. SUBQUERY Identify products ordered more than once. There was an error while loading.

Please Reload This Page. SQL-Based Ecommerce Analytics This Project Contains

Please reload this page. SQL-Based Ecommerce Analytics This project contains a complete Ecommerce SQL database with tables for customers, products, orders, and order items. The database was created, populated with sample data, and analyzed using multiple SQL queries. Key tasks include performing JOINs, aggregations, subqueries, monthly revenue analysis, identifying top-spending customers, best-sel...

Using SQLite, The Database Was Created From Scratch And Includes

Using SQLite, the database was created from scratch and includes customers, products, orders, and order item transactions. The goal is to practice real-world data analysis operations such as filtering, sorting, joining tables, aggregating values, using subqueries, creating views, and optimizing queries using indexes. 📂 Repository Structure Day 3 – Task 3 │── README.md │── sample.db (Ecommerce_SQL...

The Goal Of This Task Was To Perform SQL-based Data

The goal of this task was to perform SQL-based data analysis on an E-commerce relational database using MySQL Workbench. To analyze an E-commerce database using SQL by applying: This task demonstrates real-world SQL data analysis skills. The project uses an E-commerce dataset consisting of four relational tables: Order-level information including user ID and status. This project fulfills Task 3: S...