Data in Database is stored in terms of enormous quantity. Retrieving certain data will be a tedious task if the data is not organized correctly. With the help of Normalization, we can organize this data and also reduce the redundant data. It is the processes of reducing the redundancy of data in the table and also improving the data integrity.
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When developing the schema of a relational database, one of the most important aspects to be taken into account is to ensure that the duplication is minimized. This is done for 2 purposes:. Database Normalization is a technique that helps in designing the schema of the database in an optimal manner so as to ensure the above points.
The core idea of database normalization is to divide the tables into smaller subtables and store pointers to data rather than replicating it. To understand DBMS normalization in the database with example tables, let's assume that we are supposed to store the details of courses and instructors in a university.
Here is what a sample database could look like:. At first, this design seems to be good. However, issues start to develop once we need to modify information.
For instance, suppose, if Prof. George changed his mobile number. In such a situation, we will have to make edits in 2 places.
What if someone just edited the mobile number against CS, but forgot to edit it for CS? Basically, we store the instructors separately and in the course table, we do not store the entire data of the instructor. We rather store the ID of the instructor. Also, if we were to change the mobile number of Prof. George, it can be done in exactly one place. Further, if you observe, the mobile number now need not be stored 2 times.
We have stored it at just 1 place. This also saves storage. This may not be obvious in the above simple example. However, think about the case when there are hundreds of courses and instructors and for each instructor, we have to store not just the mobile number, but also other details like office address, email address, specialization, availability, etc. In such a situation, replicating so much data will increase the storage requirement unnecessarily.
The above is a simplified example of how database normalization works. We will now more formally study it. Each normal form has an importance which helps in optimizing the database to save storage and to reduce redundancies. The First normal form simply says that each cell of a table should contain exactly one value. Let us take an example. Suppose we are storing the courses that a particular instructor takes, we can store it like this:.
Here, the issue is that in the first row, we are storing 2 courses against Prof. A better method would be to store the courses separately. For instance:. This way, if we want to edit some information related to CS, we do not have to touch the data corresponding to CS Also, observe that each row stores unique information.
There is no repetition. This is the First Normal Form. The first point is obviously straightforward since we just studied 1NF. Let us understand the first point - 1 column primary key. Well, a primary key is a set of columns that uniquely identifies a row. Basically, no 2 rows have the same primary keys. Here, in this table, the course code is unique. So, that becomes our primary key. Let us take another example of storing student enrollment in various courses.
Each student may enroll in multiple courses. Similarly, each course may have multiple enrollments. A sample table may look like this student name and course code :. Here, the first column is the student name and the second column is the course taken by the student. Similarly, the course code column is not unique as we can see that there are 2 entries corresponding to course code CS in row 2 and row 4. However, the tuple student name, course code is unique since a student cannot enroll in the same course more than once.
So, these 2 columns when combined form the primary key for the database. To achieve the same 1NF to 2NF , we can rather break it into 2 tables:. Here the second column is unique and it indicates the enrollment number for the student. Clearly, the enrollment number is unique.
Now, we can attach each of these enrollment numbers with course codes. Before we delve into details of third normal form, let us understand the concept of a functional dependency on a table. Column A is said to be functionally dependent on column B if changing the value of A may require a change in the value of B. As an example, consider the following table:. Here, the department column is dependent on the professor name column. This is because if in a particular row, we change the name of the professor, we will also have to change the department value.
As an example, suppose MA is now taken by Prof. Ronald who happens to be from the Mathematics department, the table will look like this:. Here, when we changed the name of the professor, we also had to change the department column. This is not desirable since someone who is updating the database may remember to change the name of the professor, but may forget updating the department value.
This can cause inconsistency in the database. We can simply use the ID. Boyce-Codd Normal form is a stronger generalization of third normal form. Let us first understand what a superkey means. Here, the first column course code is unique across various rows. So, it is a superkey. Consider the combination of columns course code, professor name. It is also unique across various rows. So, it is also a superkey. A superkey is basically a set of columns such that the value of that set of columns is unique across various rows.
That is, no 2 rows have the same set of values for those columns. Some of the superkeys for the table above are:. A superkey whose size number of columns is the smallest is called as a candidate key.
For instance, the first superkey above has just 1 column. The second one and the last one have 2 columns. So, the first superkey Course code is a candidate key. A trivial functional dependency means that all columns of B are contained in the columns of A. A is a superkey: this means that only and only on a superkey column should it be the case that there is a dependency of other columns. Basically, if a set of columns B can be determined knowing some other set of columns A , then A should be a superkey.
Superkey basically determines each row uniquely. It is a trivial functional dependency: this means that there should be no non-trivial dependency.
This may lead to an inconsistent database. There are also 2 other normal forms:. A table is said to be in fourth normal form if there is no two or more, independent and multivalued data describing the relevant entity. The various forms of database normalization are useful while designing the schema of a database in such a way that there is no data replication which may possibly lead to inconsistencies. While designing the schema for applications, we should always think about how can we make use of these forms.
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View all posts by the Author. Normalization removes the duplicate data and helps to keep the data error free. At the same time, the speed of some types of operations can be slower in a non-normalized form.
Normalization increases the efficiency of the database. Basically, the 3NF is enough to remove all the anomalies from your database. Normalization removes redundant data so sometimes it increases the number of tables. There is no alternative to normalization. This depends on your application needs that it requires normalization or not.
Database Normalization Tutorial: 1NF 2NF 3NF BCNF Examples
We have a variety of advertising options which would give your courses an instant visibility to a very large set of developers, designers and data scientists. When developing the schema of a relational database, one of the most important aspects to be taken into account is to ensure that the duplication is minimized. This is done for 2 purposes:. Database Normalization is a technique that helps in designing the schema of the database in an optimal manner so as to ensure the above points. The core idea of database normalization is to divide the tables into smaller subtables and store pointers to data rather than replicating it. To understand DBMS normalization in the database with example tables, let's assume that we are supposed to store the details of courses and instructors in a university.
Normalization in DBMS: 1NF, 2NF, 3NF and BCNF with Examples
Normalization divides larger tables into smaller tables and links them using relationships. The purpose of Normalization is to eliminate redundant useless data and ensure data is stored logically. The inventor of the relational model Edgar Codd proposed the theory of normalization with the introduction of the First Normal Form, and he continued to extend theory with Second and Third Normal Form. Later he joined Raymond F. Boyce to develop the theory of Boyce-Codd Normal Form. For example, there are discussions even on 6 th Normal Form.
What is Normalization in SQL and what are its types?
The main purpose of applying the normalization technique is to reduce the redundancy and dependency of data. Normalization helps us to break down large tables into multiple small tables by defining a logical relationship between those tables. Database normalization or SQL normalization helps us to group related data in one single table. Any attributive data or indirectly related data are put in different tables and these tables are connected with a logical relationship between parent and child tables. In , Edgar F. Codd came up with the concept of normalization. By definition, an entity that does not have any repeating columns or data groups can be termed as the First Normal Form.
What is Normalization? 1NF, 2NF, 3NF & BCNF with Examples
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