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: 2026-07-07 00:26:23 UTC
- JSON Representation
https://github.com/aaleksandraristic/sqldatabase-implementation---student-admissions-portal-sap-
SQL Database Development and Implementation into Front-End Application
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SQL Thinking!
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Convert a CEL boolean expression to Squirrel SQL Builder for dynamic filtering capabilities.
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SQL statement that returns the cheapest tour using a Recursive Query
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https://github.com/demonicious/jql
Module used for Creating, Managing, Writing and Reading JSON Files and use them as a Database
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Portfolio Site applying production engineer concept on it.
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MyWorkspace
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https://github.com/anuragagarwal96/hospital-mortality-rate-sql-analysis
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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/lunardiver/smolyshortener
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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/mtumilowicz/sql-datafeed-tests
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A SQL Migration Manager that maintains database migrations scripts in an object-based structure
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https://github.com/parv-bhargava/query-quirks
"QueryQuirks" is a GitHub project that focuses on the peculiar aspects or "quirks" of database queries by analyzing the performance of databases like SQL, MongoDB, Neo4J, and Hadoop. It benchmarks these systems using Python, focusing on efficiency metrics such as time, memory, and CPU usage, and offers insights for database optimization.
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https://github.com/gaurid14/live-sql-query-explainer
JetBrains plugin to explain SQL queries inline with visual and textual breakdowns. Ideal for learning and debugging SQL.
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https://github.com/filsan-musa/project-iot_malware_identification
This repository contains the code and data for a project that detects malware from IoT devices using a publish-subscribe model with Confluent and Databricks. The project streams IoT device data to Kafka, analyzes it, and detects malware using machine learning models such as Random Forest and Gradient Boosted Trees.
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https://github.com/butttons/pg-health
Run SQL on your apple health data
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https://github.com/delarosajav/la-caprichosa
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This SQL project uses the classic Microsoft Pubs sample database. It includes queries and scripts that explore core SQL techniques such as data retrieval, filtering, joins, aggregations, and subqueries. The aim is to provide clear, hands-on examples of SQL in action using a structured, well-documented dataset.
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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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[WIP]Supports query execution by writing SQL templates in markdown.
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https://github.com/devphde/schoolmanager-api
API de gerenciamento de alunos, professores e turmas.
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https://github.com/imranxc/hackerrank-solutions
Solutions to HackerRank problems from various domains, including SQL, Python, algorithms, data structures, and more.
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https://github.com/libercosoft/vet_clinic_psgl
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https://github.com/2002bishwajeet/json-to-sql
Convert your json data to simple sql queries
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Codecademy's Career Path where I learned how to create robust and resilient data pipelines to connect data sources to analytics tools.
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OFFLINE COURSE`S PROJECTS & TASKS: PYTHON - FLASK - DJANGO - HTML - CSS - MYSQL - POSTQRESQL
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