𝗧𝗢𝗣 𝗙𝗥𝗘𝗘 𝗖𝗢𝗨𝗥𝗦𝗘𝗦 𝗧𝗢 𝗕𝗢𝗢𝗦𝗧 𝗬𝗢𝗨𝗥 𝗦𝗞𝗜𝗟𝗟𝗦 𝗜𝗡 𝟮𝟬𝟮𝟲!

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SQL Detailed Roadmap
|
| | |-- Fundamentals
| |-- Introduction to Databases
| | |-- What SQL does
| | |-- Relational model
| | |-- Tables, rows, columns
| |-- Keys and Constraints
| | |-- Primary keys
| | |-- Foreign keys
| | |-- Unique and check constraints
| |-- Normalization
| | |-- 1NF, 2NF, 3NF
| | |-- ER diagrams

| | |-- Core SQL
| |-- SQL Basics
| | |-- SELECT, WHERE, ORDER BY
| | |-- GROUP BY and HAVING
| | |-- JOINS: INNER, LEFT, RIGHT, FULL
| |-- Intermediate SQL
| | |-- Subqueries
| | |-- CTEs
| | |-- CASE statements
| | |-- Aggregations
| |-- Advanced SQL
| | |-- Window functions
| | |-- Analytical functions
| | |-- Ranking, moving averages, lag and lead
| | |-- UNION, INTERSECT, EXCEPT

| | |-- Data Management
| |-- Data Types
| | |-- Numeric, text, date, JSON
| |-- Indexes
| | |-- B tree and hash indexes
| | |-- When to create indexes
| |-- Transactions
| | |-- ACID properties
| |-- Views
| | |-- Standard views
| | |-- Materialized views

| | |-- Database Design
| |-- Schema Design
| | |-- Star schema
| | |-- Snowflake schema
| |-- Fact and Dimension Tables
| |-- Constraints for clean data

| | |-- Performance Tuning
| |-- Query Optimization
| | |-- Execution plans
| | |-- Index usage
| | |-- Reducing scans
| |-- Partitioning
| | |-- Horizontal partitioning
| | |-- Sharding basics

| | |-- SQL for Analytics
| |-- KPI calculations
| |-- Cohort analysis
| |-- Funnel analysis
| |-- Churn and retention tables
| |-- Time based aggregations
| |-- Window functions for metrics

| | |-- SQL for Data Engineering
| |-- ETL Workflows
| | |-- Staging tables
| | |-- Transformations
| | |-- Incremental loads
| |-- Data Warehousing
| | |-- Snowflake
| | |-- Redshift
| | |-- BigQuery
| |-- dbt Basics
| | |-- Models
| | |-- Tests
| | |-- Lineage

| | |-- Tools and Platforms
| |-- PostgreSQL
| |-- MySQL
| |-- SQL Server
| |-- Oracle
| |-- SQLite
| |-- Cloud SQL
| |-- BigQuery UI
| |-- Snowflake Worksheets

| | |-- Projects
| |-- Build a sales reporting system
| |-- Create a star schema from raw CSV files
| |-- Design a customer segmentation query
| |-- Build a churn dashboard dataset
| |-- Optimize slow queries in a sample DB
| |-- Create an analytics pipeline with dbt

| | |-- Soft Skills and Career Prep
| |-- SQL interview patterns
| |-- Joins practice
| |-- Window function drills
| |-- Query writing speed
| |-- Git and GitHub
| |-- Data storytelling

| | |-- Bonus Topics
| |-- NoSQL intro
| |-- Working with JSON fields
| |-- Spatial SQL
| |-- Time series tables
| |-- CDC concepts
| |-- Real time analytics

| | |-- Community and Growth
| |-- LeetCode SQL
| |-- Kaggle datasets with SQL
| |-- GitHub projects
| |-- LinkedIn posts
| |-- Open source contributions

Free Resources to learn SQL

• W3Schools SQL
https://www.w3schools.com/sql/

• SQL Programming
https://whatsapp.com/channel/0029VanC5rODzgT6TiTGoa1v

• SQL Notes
https://whatsapp.com/channel/0029Vb6hJmM9hXFCWNtQX944

• Mode Analytics SQL tutorials
https://mode.com/sql-tutorial/

• Data Analytics Resources
https://t.me/sqlspecialist

• HackerRank SQL practice
https://www.hackerrank.com/domains/sql

• LeetCode SQL problems
https://leetcode.com/problemset/database/

• Data Engineering Resources
https://whatsapp.com/channel/0029Vaovs0ZKbYMKXvKRYi3C

• Khan Academy SQL basics
https://www.khanacademy.org/computing/computer-programming/sql

• PostgreSQL official docs
https://www.postgresql.org/docs/

• MySQL official docs
https://dev.mysql.com/doc/

• NoSQL Resources
https://whatsapp.com/channel/0029VaxA2hTHgZWe5FpFjm3p

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A – API

Set of rules allowing different apps to communicate, like fetching data from servers.

B – Bootstrap

Popular CSS framework for responsive, mobile-first front-end development.

C – CSS

Styles web pages with layouts, colors, fonts, and animations for visual appeal.

D – DOM

Document Object Model; tree structure representing HTML for dynamic manipulation.

E – ES6+

Modern JavaScript features like arrows, promises, and async/await for cleaner code.

F – Flexbox

CSS layout module for one-dimensional designs, aligning items efficiently.

G – GitHub

Platform for version control and collaboration using Git repositories.

H – HTML

Markup language structuring content with tags for headings, links, and media.

I – IDE

Integrated Development Environment like VS Code for coding, debugging, tools.

J – JavaScript

Language adding interactivity, from form validation to full-stack apps.

K – Kubernetes

Orchestration tool managing containers for scalable web app deployment.

L – Local Storage

Browser API storing key-value data client-side, persisting across sessions.

M – MongoDB

NoSQL database for flexible, JSON-like document storage in MEAN stack.

N – Node.js

JavaScript runtime for server-side; powers back-end with npm ecosystem.

O – OAuth

Authorization protocol letting apps access user data without passwords.

P – Progressive Web App

Web apps behaving like natives: offline, push notifications, installable.

Q – Query Selector

JavaScript/DOM method targeting elements with CSS selectors for manipulation.

R – React

JavaScript library for building reusable UI components and single-page apps.

S – SEO

Search Engine Optimization improving site visibility via keywords, speed.

T – TypeScript

Superset of JS adding types for scalable, error-free large apps.

U – UI/UX

User Interface design and User Experience focusing on usability, accessibility.

V – Vue.js

Progressive JS framework for reactive, component-based UIs.

W – Webpack

Module bundler processing JS, assets into optimized static files.

X – XSS

Cross-Site Scripting vulnerability injecting malicious scripts into web pages.

Y – YAML

Human-readable format for configs like Docker Compose or GitHub Actions.

Z – Zustand

Lightweight state management for React apps, simpler than Redux.

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𝗠𝗜𝗖𝗥𝗢𝗦𝗢𝗙𝗧 𝗙𝗥𝗘𝗘 𝗗𝗔𝗧𝗔 𝗦𝗖𝗜𝗘𝗡𝗖𝗘 𝗥𝗘𝗦𝗢𝗨𝗥𝗖𝗘𝗦 𝟮𝟬𝟮𝟲! 🎓

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📅 Date:- 23 October 2026
⏰ Time:- 7:00 PM–9:00 PM IST
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