SQL Data Analysis for beginners: MS SQL | SQL Server | SSMS

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  • Reading time:8 mins read


Master real World Data Analysis with SQL

What you will learn

Extract | Combine Data From Different Tables

Sorting Data

Filtering Data

Aggregating and Grouping Data

Data Analysis using SET Operators

Data Analysis using Analytic Functions

Build 27 Real World Data Analysis SQL Queries

Description

The volume of data available is huge and increasing daily. Structured Query Language -SQL (pronounced as sequel) is the standard language used to communicate and interact with data stored in relational management database systems like Microsoft  SQL Server Oracle, PostgreSQL,MySQL etc.

Different database management systems have their own proprietary  version of the SQL language  but they all conform to using some commands in SQL the same way.   Microsoft SQL Server’s version of SQL is known as Transact-SQL  (T-SQL).    In this course you will learn the basics of the SQL language and Transact-SQL since  both use certain commands in the same way.


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T-SQL is also popularly referenced to as T-Sequel .In this course you will learn all the basics of T-SQL. We will discuss the T-SQL features step by step. We will be using SQL Server Express 2014 (which is a free download). As a sample, we will use AdventureWorks 2014 as our database. Along the way, we will be creating our own t-SQL queries to get data into a database and also out of a database.  But AdventureWorks 2014 will be our main focus. As far as T-SQL, we will start with the simple select statements and add new features as we go. I will introduce you to the data types available so you can make the appropriate selection when creating a column. Then, we will talk about joins, functions, tables, procedures, triggers, indexes, and much more. By the time you are done with this course, you will be very comfortable using T-SQL.
This course will provide you with the basic knowledge and skills to create queries using Transact-SQL. It will teach you how to select, filter and sort data from multiple tables and how to use views and stored procedures. You will also be familiar with SQL Server Management Studio 2014 also known in the tech industry as SSMS. This is the tool you will use to write and see the output of your T-SQL queries.

English
language

Content

SQL Server Setup
Introduction
What is SQL Server
What is SQL
What is MS SQL (T-SQL)
SQL Server Hardware and Software Requirements
SQL Server Editions
Download SQL Server
Install SQL Server
Install SSMS
Connect SSMS to SQL Server
Install Sample database
Basic database concepts
Filtering Data
Introduction
Filtering data with basic equality filters
Filtering data with basic comparisons
Filtering data with logical comparisons
Filtering data with String Comparisons
Filtering data with NULL Comparisons
Sorting Data
Introduction
Order By Clause
Sorting by ascending
Sorting by descending
Sorting by multiple columns
Extract | Combine Data From Different Tables
Introduction
Why Table Joins are necessary
Using INNER Join
Using LEFT Outer Join
Using Right Outer Join
Aggregating and Grouping Data
Introduction
Using COUNT ( ) Aggregate Function
Using AVG ( ) Aggregate Function
Using MAX ( ) Aggregate Function
Using MIN ( ) Aggregate Function
Using SUM ( ) Aggregate Function
Using VAR Function
Using VARP Function
Using Multiple Aggregate Functions
Grouping Data
Data Analysis using SET Operators
What are SET Operators
Query Data with EXCEPT
Query Data with INTERSECT
Query Data with UNION
Data Analysis using Analytic Functions
What are Analytic Functions
Syntax for Analytic Functions
CUME_DIST Function
Row Number Functions
Rank Functions
NTILE Function
Using LEAD Function
Using the LAG Function
Using FIRST_VALUE Function
Using LAST_VALUE Function
Using PERCENT_RANK Function
Using PERCENT_COUNT Function
Using PERCENTILE_DISC Function
27 Real World Data Analysis SQL Queries
Download Sample Database
Install Sample Database
Data Analysis of Countries with Customers
Data Analysis of Customer Contact Titles
Data Analysis of Customers and Employee Count
Data Analysis of Employee Full Name
Data Analysis of Customer First Order
Data Analysis of discontinued products
Data Analysis of Shippers
Data Analysis of Most and least expensive products
Data Analysis of Orders placed
Data Analysis of Orders shipped to specific countries
Data Analysis of products stock
Data Analysis of specific products
Data Analysis of Total price
Data Analysis of Sales Reps
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