SQL For Data Analyst and Data Engineer
SQL For Data Analyst and Data Engineer, available at $19.99, with 124 lectures, 5 quizzes, and has 3 subscribers.
You will learn about 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 This course is ideal for individuals who are Working Professionals beginning their Data journey or Data Analyst or Anyone curious to master SQL from beginner to Advanced in short span of time or Students or Professional looking for Job as Data Analyst It is particularly useful for Working Professionals beginning their Data journey or Data Analyst or Anyone curious to master SQL from beginner to Advanced in short span of time or Students or Professional looking for Job as Data Analyst.
Enroll now: SQL For Data Analyst and Data Engineer
Summary
Title: SQL For Data Analyst and Data Engineer
Price: $19.99
Number of Lectures: 124
Number of Quizzes: 5
Number of Published Lectures: 122
Number of Published Quizzes: 5
Number of Curriculum Items: 130
Number of Published Curriculum Objects: 128
Original Price: $19.99
Quality Status: approved
Status: Live
What You Will 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
Who Should Attend
- 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
Target Audiences
- 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
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:
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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.
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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.
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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.
Course Curriculum
Chapter 1: Introduction
Lecture 1: Introduction
Lecture 2: Connect to SQL Server
Chapter 2: Data Definition Language
Lecture 1: DataBase
Lecture 2: Create Schema
Lecture 3: Alter Schema
Lecture 4: Create Table
Lecture 5: Add Column
Lecture 6: Change Column Data Type
Lecture 7: Compute Column
Lecture 8: Drop Column
Lecture 9: Truncate Table
Lecture 10: Drop Table
Lecture 11: Local Temp Table
Lecture 12: Global Temp Table
Chapter 3: Basic SQL Statement
Lecture 1: Basic SQL Syntax
Lecture 2: Order of Query Execution
Chapter 4: SQL Data Type
Lecture 1: SQL Data Type Intro
Lecture 2: BIT
Lecture 3: Integer
Lecture 4: Char and Varchar
Lecture 5: Date Time
Lecture 6: GUID
Chapter 5: Data Manipulation Language
Lecture 1: Insert Data in Table
Lecture 2: Insert Data From Another Table
Lecture 3: Insert Top N Value
Lecture 4: Insert Top N Percent Value
Lecture 5: Update Rows
Lecture 6: Update Rows From Another Table
Lecture 7: Delete
Lecture 8: Delete Top N Rows
Lecture 9: Delete Top N Percent
Chapter 6: Identity and Sequence
Lecture 1: Identity
Lecture 2: Sequence and Sequence vs identity column
Chapter 7: Truncate and Truncate Vs Delete
Lecture 1: Truncate
Lecture 2: Truncate Vs Delete
Chapter 8: Constraint in SQL
Lecture 1: Primary Key on Single Column
Lecture 2: Primary Key On Multiple Column
Lecture 3: Primary Key On Existing Table
Lecture 4: Foreign Key
Lecture 5: Foreign Key Example
Lecture 6: Action On Child Table When Update on Parent Table
Lecture 7: Action On Child Table When Delete On Parent Table
Lecture 8: Unique Key
Lecture 9: Unique Key On Multiple Column
Lecture 10: Unique Key On Existing Table
Lecture 11: Check Constraint
Lecture 12: Drop Check Constraint
Chapter 9: Limiting the Rows
Lecture 1: OFFSET and Fetch
Lecture 2: Top with Percentage
Chapter 10: Filtering Data
Lecture 1: Distinct
Lecture 2: Where Clause with Equal and Not Equal
Lecture 3: Where Clause with <,>,>=,<= Operator
Lecture 4: Where Clause with not like Operator
Lecture 5: Where Clause with like Operator
Lecture 6: Where Clause with and, Or
Lecture 7: Where Clause with Null
Lecture 8: Where Clause with Exist and Not Exist
Chapter 11: Joining Table
Lecture 1: Left Join
Lecture 2: Right Join
Lecture 3: Inner Join
Lecture 4: Cross Join
Lecture 5: Full Outer Join
Lecture 6: Advance or Intelligent Join
Chapter 12: Grouping Data
Lecture 1: Group by
Lecture 2: Group By With Aggregate
Lecture 3: Cube
Lecture 4: Roll UP
Lecture 5: Group By with Where and Having Clause
Lecture 6: Group by with Grouping Set
Chapter 13: Sub Query
Lecture 1: Sub Query
Lecture 2: Nested Sub Query
Lecture 3: Subquery with Exist and Not Exist
Lecture 4: Sub Query with Any and All
Lecture 5: CO-Related Sub Query
Lecture 6: Sub Query in Expression
Lecture 7: Sub Query in From Clause
Chapter 14: Set Operator
Lecture 1: Union and Union All
Lecture 2: Intersection
Lecture 3: Except
Chapter 15: Common Table Expression
Lecture 1: Common Table Expression
Instructors
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Sonu Kumar
Instructor at Udemy
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Frequently Asked Questions
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You can view and review the lecture materials indefinitely, like an on-demand channel.
Can I take my courses with me wherever I go?
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