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SQL For Data Analyst and Data Engineer
Rating: 2.1 out of 5(8 ratings)
26 students

SQL For Data Analyst and Data Engineer

BI and Data Engineer
Created bySonu Kumar
Last updated 3/2025
English

What you'll learn

  • SQL Query for Data Analysis
  • Basic SQL Syntax
  • SQL Join
  • Limiting Row
  • Filtering Data
  • Set Operation
  • Subquery
  • Grouping Data
  • Common Table Expression
  • Pivot in SQL
  • Expression in SQL Server
  • Function in SQL
  • Window and Rank Function
  • Regex in SQL
  • SQL Interview Question
  • View
  • Store Procedure
  • Data Definition Language
  • Data Manipulation Language
  • Constraint
  • Sequence and Identity
  • Trigger
  • Dynamic SQL Query
  • Partition
  • Copy Data From File To Table

Course content

26 sections124 lectures8h 7m total length
  • Introduction6:24
  • Connect to SQL Server2:49

Requirements

  • NO experience needed, Any one can learn this Course

Description

SQL is the most widely used language for data analysis and manipulation. Whether you are a data analyst, data scientist, marketer, engineer, or product manager, knowing SQL will help you access and work with data more efficiently and effectively.

In this course, you will learn the basics of SQL and how to use it for various data analysis tasks. You will learn how to write common SQL commands, such as SELECT, FROM, WHERE, JOIN, and GROUP BY. You will also learn how to use more advanced features of SQL, such as subqueries, temp tables, window functions, and date functions.

By the end of this course, you will be able to write SQL queries to extract, transform, and analyze data from any relational database. You will also be able to apply your SQL skills to real-world scenarios and projects.

This course is designed for beginners an Professional who have some familiarity with data in spreadsheets. No prior programming experience is required. All you need is a computer and an internet connection.

Join this course today and start your journey to becoming a SQL expert!?


SQL is used in many real-world scenarios where data is stored in relational databases and needs to be accessed, manipulated, or analyzed. Here are some examples:


  • E-commerce websites use SQL to store product information, customer details, orders, payments, and reviews. For example, Amazon uses MySQL, a popular relational database management system, for its online transactions.

  • Social media networks use SQL to store user information, posts, comments, likes, shares, and messages. For example, Facebook uses MySQL for its primary data storage and Hive for its data warehouse.

  • Educational institutions use SQL to store student records, grades, courses, enrollments, and attendance. For example, Stanford University uses Oracle Database, a powerful relational database management system, for its administrative and academic functions.

Who this course is for:

  • Working Professionals beginning their Data journey
  • Data Analyst
  • Anyone curious to master SQL from beginner to Advanced in short span of time
  • Students or Professional looking for Job as Data Analyst