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What you'll learn?
- Student will be able to Understand the core concept of SQL and How to use it as a Data Analyst or Data Engineer
Course Overview
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.
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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.
Pre-requisites
- Any one can join Course and Understand the Core Concept of Data
Target Audience
- Working Professionals beginning their Data journey
- Anyone curious to master SQL from beginner to Advanced in short span of time
- Data Analyst
Curriculum 117 Lectures 07:28:54
-
Section 1 : Introduction
- Lecture 2 :
- Connect To SQL Server
-
Section 2 : Data Definition Language
- Lecture 1 :
- Data Base
- 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
-
Section 3 : SQL Data Type
- Lecture 1 :
- SQL Server Data Type Into
- Lecture 2 :
- BIT
- Lecture 3 :
- Integer
- Lecture 4 :
- Char and Varchar
- Lecture 5 :
- Date Time
- Lecture 6 :
- GUID
-
Section 4 : Constraint
- 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
-
Section 5 : Temp Table
- Lecture 1 :
- Local Temp Table
- Lecture 2 :
- Global Temp Table
-
Section 6 : Limiting The Rows
- Lecture 1 :
- Offset and Fetch
- Lecture 2 :
- Top With Percentage and Ties
-
Section 7 : 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
-
Section 8 : 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
-
Section 9 : Group By
- Lecture 1 :
- Group BY
- Lecture 2 :
- Group By With Aggregate
- Lecture 3 :
- Cube
- Lecture 4 :
- Group By with Where and Having Clause
- Lecture 5 :
- Group by with Grouping Set
-
Section 10 : 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
-
Section 11 : Set Operator
- Lecture 1 :
- Union and Union All
- Lecture 2 :
- Intersection
- Lecture 3 :
- Except
-
Section 12 : 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
-
Section 13 : Truncate and Truncate Vs Delete
- Lecture 1 :
- Truncate
-
Section 14 : Identity and Sequence
- Lecture 1 :
- Identity
- Lecture 2 :
- Sequence and Sequence vs identity column
-
Section 15 : Common Table Expression
- Lecture 1 :
- Common Table Expression
- Lecture 2 :
- Recursive Common Table Expression
- Lecture 3 :
- Multiple CTE in SQL Server
-
Section 16 : Pivot Table
- Lecture 1 :
- Pivot Table
-
Section 17 : Function in SQL
- Lecture 1 :
- String Function
- Lecture 2 :
- Date and Time Function
- Lecture 3 :
- User Defined Function
- Lecture 4 :
- Inline Table Value Function
- Lecture 5 :
- Multi Statement Table Value Function
-
Section 18 : Window or Analytics Function
- Lecture 1 :
- Rank Function
- Lecture 2 :
- First and Last
- Lecture 3 :
- Lead and Lag
- Lecture 4 :
- CUM Distributive Function
- Lecture 5 :
- NTILE Function
-
Section 19 : View in SQL
- Lecture 1 :
- View Definition
- Lecture 2 :
- View
- Lecture 3 :
- Advantage Of View
- Lecture 4 :
- Materialized View
-
Section 20 : Store Procedure in SQL
- Lecture 1 :
- Store Procedure and Its Benefit
- Lecture 2 :
- Store Procedure Without Parameter
- Lecture 3 :
- Store Procedure With Input Parameter
- Lecture 4 :
- Store Procedure With Input Default Parameter
- Lecture 5 :
- Store Procedure with Out Put Parameter
- Lecture 6 :
- Temporary Store Procedure
- Lecture 7 :
- Store Procedure with Encryption
- Lecture 8 :
- Modify Store Procedure
-
Section 21 : Normalization
- Lecture 1 :
- Normalization
-
Section 22 : Regex in SQL
- Lecture 1 :
- Regex Starts With
- Lecture 2 :
- Regex Ends with
- Lecture 3 :
- Regex with Exclude Character
- Lecture 4 :
- Regex with Specific Pattern
-
Section 23 : Expression In SQL
- Lecture 1 :
- Case Statement
- Lecture 2 :
- Is Null
- Lecture 3 :
- Null If
-
Section 24 : Trigger
- Lecture 1 :
- Trigger
- Lecture 2 :
- Instead of Insert
- Lecture 3 :
- After Insert
- Lecture 4 :
- Instead of Delete
- Lecture 5 :
- After Delete
- Lecture 6 :
- Instead of Update
- Lecture 7 :
- After Update
- Lecture 8 :
- DDL trigger
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