SQL
SQL stands for structured query language. It uses commands such as “select”, “insert”, “update”, “delete”. Some common relational database management systems that use SQL are: Oracle, MySQL, Microsoft SQL Server, PostgreSQL, etc.
- GitHub: https://github.com/topics/sql
- Wikipedia: https://en.wikipedia.org/wiki/SQL
- Created by: Donald D. Chamberlin, Raymond F. Boyce
- Released: 1986
- Related Topics: database,
- Last updated: 2026-07-09 00:25:54 UTC
- JSON Representation
https://github.com/oleksandr-romashko/goit-rdb-hw-02
Designing Relational Databases Using Semantic Models: ER Diagrams
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https://github.com/byn227/accidents_in_france
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https://github.com/mdalamin5/play-with-sql-from-scratch
A complete hands-on SQL practice repo based on CampusX's DBMS & SQL course. Covers DDL, DML, Grouping, Joins, Subqueries, and Window Functions using MySQL. Ideal for beginners to strengthen their database skills with real-world datasets and structured folder-wise queries.
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Run SQL queries directly from the Xperience by Kentico administration
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https://github.com/danikohub/sqlaboratory
Class to make working with SQL ORM faster and easier
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https://github.com/feedboards/feedboards.json.sqlify
A library for generating SQL code based on the structure of any JSON files.
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https://github.com/anand-gith/tinyhub
Design and Build Database for a Tinyhub - Student Application
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https://github.com/shridhar1504/sql-projects
The repository contains Structured Query Language (SQL) Scripts. The Multiple SQL scripts for various projects which includes data cleaning, data pre-processing, data processing, data transformation and insights gaining through Query Language.
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https://github.com/shanukatiyar111/create_calendar_in_sql
CREATED CALENDAR IN SQL SERVER
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https://github.com/naninsv/marketing-analytics
The Marketing Analytics Project focuses on analyzing customer engagement, conversion rates, and sentiment trends to optimize marketing strategies for ShopEasy. Using SQL, Python (NLTK), and Power BI, this project extracts insights from customer reviews, transactions, and social media interactions to identify key areas for improvement.
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Analyze order data to identify the most and least popular menu items and types of cuisine
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https://github.com/thomasjvu/codewars
❓ Answers and explanations for my daily Codewars practice problems
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https://github.com/tashi-2004/Database-Systems-DB
I've created files with solutions, named them with their following conventions and order. You can download, copy, and run them on a compiler or software for your information. There are no copyrights attached to these files; they are provided for educational purposes only.
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https://github.com/paulf-999/sql_templates
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https://github.com/valeriogc/db-videogames-query
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https://github.com/simoesleticia/sql-server-data-import-export
O propósito deste repositório é demonstrar o processo de importação e exportação de dados utilizando Microsoft SQL Server, com foco em arquivos nos formatos .CSV e .JSON.
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https://github.com/joshdabestlol/cinevision
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Software | SQL Database with automated Cloud Sync for mitigating lost data across dist. servers. Managed by Ruby on Rails.
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Análisis de datos que explorar y visualizar atributos de empleados (como sueldo, género) utilizando herramientas como SQL y Tableau.
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https://github.com/bell-kevin/sdev1041sqlfinalproject
What is the store’s average days for a customer to pay based on the return date of the film and the payment date. What is the customer’s average? Show a list of customer names, store id, customer’s average day to pay, and store’s average day to pay. Filter the results by customers that have an average days out greater than the stores average. Order the results by the customer ID. (Hint: stores have inventory, inventory have rentals, and rentals have payments.) Please add the function NOW() and give it a column name of your first name and last name separated by a underscore (this should be the first output column).
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Extracts data from a spreadsheet and outputs its contents to a '.SQL' file. Data extraction tool useful for people using SQL Server Express with no access to SSMS addon and import wizard.
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https://github.com/croketillo/sqlite-explorer
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https://github.com/shivanshkumar760/sqlyapper
SQLYAPPER is a web application that helps users generate SQL queries using the power of GPT models. Simply provide a natural language description of the desired query, and SQLYAPPER will translate it into accurate SQL code.
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https://github.com/sqlthinking/sqlthinking.github.io
SQL Thinking!
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SQLInjection
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https://github.com/haideratgh/sql-data-analytics-project
This repository contains a collection of SQL scripts demonstrating various analytical techniques, such as changes over time, cumulative, performance, data segmentation, part-to-whole analysis
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https://github.com/gzixnine/hospital_management_system
This repository contains a comprehensive database schema designed for a Hospital Management System to manage various aspects of healthcare operations efficiently. The project is built with a focus on scalability, data integrity, and ease of use for medical staff and administrators.
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This course serves as an introduction to Structured Query Language (SQL) for the aspiring data professional, focusing on fundamental concepts and practical applications. The course incorporates interactive video lectures, as well as weekly course exercises to reinforce learning.
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Automated Data Pipeline that ingests daily GA4-formatted CSV files from a private Google Cloud Storage bucket, validates and loads them into BigQuery, and prepares analysis-ready views. The solution is built for deployment as a Cloud Function triggered by Cloud Scheduler and uses Python with the Google Cloud Storage and BigQuery client libraries.
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Modelling Vaccine Distribution in Finland with PostgreSQL database
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https://github.com/davidsilva32/db-enfermagem-clientes
Este repositório contém o código e a documentação para o Sistema de Banco de Dados para Técnicos de Enfermagem. O projeto foi desenvolvido para ajudar técnicos de enfermagem a gerenciar de forma eficiente as informações de seus pacientes, medicamentos administrados e os pagamentos recebidos de cada cliente.
Last synced: 14 Feb 2026
