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What is Normalization? 

What is Normalization? 

Normalization is a database design technique which organizes tables in a manner that reduces redundancy and dependency of data.

It divides larger tables to smaller tables and link them using relationships.

In this tutorial, you will learn-

The inventor of the relational model Edgar Codd proposed the theory of normalization with the introduction of First Normal Form and he continued to extend theory with Second and Third Normal Form. Later he joined with Raymond F. Boyce  to develop the theory of Boyce-Codd Normal Form.

Theory of Data Normalization in Sql is still being developed further. For example there are discussions even on 6th Normal Form. But in most practical applications normalization achieves its best in 3rd Normal Form. The evolution of Normalization theories is illustrated below

1st Normal Form >> 2nd Normal Form >> 3rd Normal Form >>4th Normal Form >>  5th Normal Form >>6th Normal Form

Database Normalization Examples –

Assume a video library maintains a database of movies rented out. Without any normalization all information is stored in one table as shown below.

Further We shall discuss on different normal forms in detailed:

 

 

 

 

 

 

How to use INNER JOIN in SQL Server?

The most frequently used and important of the joins is the INNER JOIN. They are also referred to as an EQUIJOIN.

The INNER JOIN creates a new result table by combining column values of two tables (table1 and table2) based upon the join-predicate. The query compares each row of table1 with each row of table2 to find all pairs of rows which satisfy the join-predicate. When the join-predicate is satisfied, column values for each matched pair of rows of A and B are combined into a result row.

Syntax: The basic syntax of INNER JOIN is as follows:

SELECT table1.column1, table2.column2…
FROM table1
INNER JOIN table2
ON table1.common_field = table2.common_field;

Image Representation:

The INNER JOIN in SQL joins two tables according to the matching of a certain criteria using a comparison operator.

Sample Two Table Data:

FOODS:

 ITEM_ID ITEM_NAME ITEM_UNIT COMPANY_ID
1 Bread PCS 25
2 Sliced Bread PCS 16
3 Roasted Bread PCS 32
4 Garlic Bread PCS 48
5 Cheese Bread PCS 18
6 Fruit Bread PCS 22
7 Milk Bread PCS 28

Company:

COMPANY_ID COMPANY_NAME COMPANY_CITY
25 SUBWAY IRLAND
16 BURGER KING UNITED STATES
32 KFC UK
18 ROLLZONE AUSTRALIA
28 DOMINOS INDIA

Example

Here is an example of inner join in SQL between two tables.

To join item name, item unit columns from foods table and company name, company city columns from company table, with the following condition –

1. company_id of foods and company_id company table must be same, the following SQL statement can be used :

SELECT foods.item_name,foods.item_unit,
company.company_name,company.company_city
FROM foods
INNER JOIN company
ON foods.company_id =company.company_id;

Example of SQL INNER JOIN using JOIN keyword

To get item name, item unit columns from foods table and company name, company city columns from company table, after joining these mentioned tables, with the following condition –

1. company id of foods and company id of company table must be same,

the following SQL statement can be used :
SELECT foods.item_name,foods.item_unit,
company.company_name,company.company_city
FROM foods
JOIN company
ON foods.company_id =company.company_id;

SQL Server next version CTP 1.4

Microsoft is excited to announce a new preview for the next version of SQL Server (SQL Server v.Next). Community Technology Preview (CTP) 1.4 is available on both Windows and Linux. In this preview, they added the ability to schedule jobs using SQL Server Agent on Linux. We can try the preview in your choice of development and test environments now: www.sqlserveronlinux.com.

Key CTP 1.4 enhancements
The primary enhancement to SQL Server v.Next on Linux in this release is the ability to schedule jobs using SQL Server Agent. This functionality helps administrators automate maintenance jobs and other tasks, or run them in response to an event. Some SQL Server Agent functionality is not yet enabled for SQL Server on Linux. To learn more and see sample SQL Server Agent jobs, you can read detailed blog titled “SQL Server on Linux: Running scheduled jobs with SQL Server Agent” or attend an Engineering Town Hall about “SQL Server Agent and Full Text Search in SQL Server on Linux.”

The mssql-server-linux container image on Docker Hub now includes the sqlcmd and bcp command line utilities to make it easier to create and attach databases and automate other actions when working with containers. For additional detail on CTP 1.4, please visit What’s New in SQL Server v.Next, Release Notes and Linux
documentation.

In addition, SQL Server Analysis Services and SQL Server Reporting Services developer tools now support Visual Studio 2017. They are available for installation from the Visual Studio Marketplace providing the option for automatic updates going forward.

 

Get SQL Server v.Next CTP 1.4 today!
Try the preview of the next release of SQL Server today! Get started with the preview of SQL Server with our developer tutorials that show you how to install and use SQL Server v.Next on macOS, Docker, Windows, and Linux and quickly build an app in a programming language of your choice.

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