Which is used to eliminate insertion updation and deletion anomalies?
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Database Normalization is a technique of organizing the data in the database. Normalization is a systematic approach of decomposing tables to eliminate data redundancy(repetition) and undesirable characteristics like Insertion, Update and Deletion Anomalies. It is a multi-step process that puts data into tabular form, removing duplicated data from the relation tables. Show
Normalization is used for mainly two purposes,
The video below will give you a good overview of Database Normalization. If you want you can skip the video, as the concept is covered in detail, below the video. Problems Without NormalizationIf a table is not properly normalized and have data redundancy then it will not only eat up extra memory space but will also make it difficult to handle and update the database, without facing data loss. Insertion, Updation and Deletion Anomalies are very frequent if database is not normalized. To understand these anomalies let us take an example of a Student table.
In the table above, we have data of 4 Computer Sci. students. As we can see, data for the fields branch, hod(Head of Department) and office_tel is repeated for the students who are in the same branch in the college, this is Data Redundancy. Insertion AnomalySuppose for a new admission, until and unless a student opts for a branch, data of the student cannot be inserted, or else we will have to set the branch information as NULL. Also, if we have to insert data of 100 students of same branch, then the branch information will be repeated for all those 100 students. These scenarios are nothing but Insertion anomalies. Updation AnomalyWhat if Mr. X leaves the college? or is no longer the HOD of computer science department? In that case all the student records will have to be updated, and if by mistake we miss any record, it will lead to data inconsistency. This is Updation anomaly. Deletion AnomalyIn our Student table, two different informations are kept together, Student information and Branch information. Hence, at the end of the academic year, if student records are deleted, we will also lose the branch information. This is Deletion anomaly. Normalization RuleNormalization rules are divided into the following normal forms:
First Normal Form (1NF)For a table to be in the First Normal Form, it should follow the following 4 rules:
In the next tutorial, we will discuss about the First Normal Form in details. Second Normal Form (2NF)For a table to be in the Second Normal Form,
To understand what is Partial Dependency and how to normalize a table to 2nd normal for, jump to the Second Normal Form tutorial. Third Normal Form (3NF)A table is said to be in the Third Normal Form when,
Here is the Third Normal Form tutorial. But we suggest you to first study about the second normal form and then head over to the third normal form. Boyce and Codd Normal Form (BCNF)Boyce and Codd Normal Form is a higher version of the Third Normal form. This form deals with certain type of anomaly that is not handled by 3NF. A 3NF table which does not have multiple overlapping candidate keys is said to be in BCNF. For a table to be in BCNF, following conditions must be satisfied:
To learn about BCNF in detail with a very easy to understand example, head to Boye-Codd Normal Form tutorial. Fourth Normal Form (4NF)A table is said to be in the Fourth Normal Form when,
Here is the Fourth Normal Form tutorial. But we suggest you to understand other normal forms before you head over to the fourth normal form. What is insert update and delete anomaly?There are three types of anomalies: update, deletion, and insertion anomalies. An update anomaly is a data inconsistency that results from data redundancy and a partial update. For example, each employee in a company has a department associated with them as well as the student group they participate in.
How can data anomalies be eliminated?How can such anomalies be eliminated? The most common anomalies considered when data redundancy exists are: update anomalies, addition anomalies, and deletion anomalies. All these can easily be avoided through data normalization.
How are insert anomalies prevented?The simplest way to avoid update anomalies is to sharpen the concepts of the entities represented by the data sets. In the preceding example, the anomalies are caused by a blending of the concepts of orders and products. The single data set should be split into two data sets, one for orders and one for products.
What is anomalies and how they are removed explain with example?A database anomaly is a fault in a database that usually emerges as a result of shoddy planning and storing everything in a flat database. In most cases, this is removed through the normalization procedure, which involves the joining and splitting of tables.
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