SQL For Data Analyst and Data Engineer

BI and Data Engineer

Created by : Rated :4.5 819 views

Last Updated: 2023-12-18 07:12:14 English Course Type: Self Learning

Student will be able to Understand the core concept of SQL and How to use it as a Data Analyst or Data Engineer

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.

Any one can join Course and Understand the Core Concept of Data

Working Professionals beginning their Data journey
Anyone curious to master SQL from beginner to Advanced in short span of time
Data Analyst

Section 1 : Introduction 2 Lectures 00:09:13
Lecture 1 :
Introduction Preview
Lecture 2 :
Connect To SQL Server
Section 2 : Data Definition Language 10 Lectures 00:26:35
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 6 Lectures 00:12:06
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 12 Lectures 00:42:30
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 2 Lectures 00:12:38
Lecture 1 :
Local Temp Table
Lecture 2 :
Global Temp Table
Section 6 : Limiting The Rows 2 Lectures 00:11:33
Lecture 1 :
Offset and Fetch
Lecture 2 :
Top With Percentage and Ties
Section 7 : Filtering Data 8 Lectures 00:32:33
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 6 Lectures 00:22:53
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 5 Lectures 00:17:02
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 7 Lectures 00:25:51
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 3 Lectures 00:09:14
Lecture 1 :
Union and Union All
Lecture 2 :
Intersection
Lecture 3 :
Except
Section 12 : Data Manipulation Language 9 Lectures 00:20:17
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 1 Lectures 00:01:17
Lecture 1 :
Truncate
Section 14 : Identity and Sequence 2 Lectures 00:09:16
Lecture 1 :
Identity
Lecture 2 :
Sequence and Sequence vs identity column
Section 15 : Common Table Expression 3 Lectures 00:11:52
Lecture 1 :
Common Table Expression
Lecture 2 :
Recursive Common Table Expression
Lecture 3 :
Multiple CTE in SQL Server
Section 16 : Pivot Table 1 Lectures 00:05:30
Lecture 1 :
Pivot Table
Section 17 : Function in SQL 5 Lectures 00:44:14
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 5 Lectures 00:22:08
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 4 Lectures 00:12:29
Lecture 1 :
View Definition
Lecture 2 :
View
Lecture 3 :
Advantage Of View
Lecture 4 :
Materialized View
Section 20 : Store Procedure in SQL 8 Lectures 00:26:16
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 1 Lectures 00:09:16
Lecture 1 :
Normalization
Section 22 : Regex in SQL 4 Lectures 00:18:04
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 3 Lectures 00:07:06
Lecture 1 :
Case Statement
Lecture 2 :
Is Null
Lecture 3 :
Null If
Section 24 : Trigger 8 Lectures 00:39:01
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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