A candidate key is an important concept in database normalization. Read on to find out what a candidate key is and how to check if a set of attributes is a candidate key. The candidate key, also simply called a key, is an important part of database design. It is the theoretical foundation for technical concepts like primary and alternate (unique) keys. Every database designer should be aware of how to identify candidate keys and how to choose the right one for their table.
Do you know what a closure of a set of attributes is? Do you know how to find it? This knowledge is essential for database normalization. In this article, learn what a closure of a set of attributes is and how to find it with real-world examples. Finding the closure of a set of attributes is an important topic for relational databases. The closure of a set of attributes is taught in every university database class.
Database Normalization in Simple English Have you heard of 2NF, 3NF, and BCNF? Do you know what the database normal forms mean? In this article, you will learn database normalization in simple English. With real-world examples, you will better understand what normal forms are, why there are different types, and why we need them. Database courses typically teach database normalization and normal forms abstractly. Functional dependencies and normalization problems are defined using letters (e.
Normalization in Relational Databases: First Normal Form (1NF), Second Normal Form (2NF), and Third Normal Form (3NF)
What is database normalization? What are the different normal forms, and what do they do? Find out in this article. Normalization in relational databases is a design process that minimizes data redundancy and avoids update anomalies. Basically, you want each piece of information to be stored exactly once; if the information changes, you only have to update it in one place. The theory of normal forms gives rigorous meaning to these informal concepts.
In the previous two articles, we considered the two most common data warehouse models: the star schema and the snowflake schema. Today, we’ll examine the differences between these two schemas and we’ll explain when it’s better to use one or the other. The star schema and the snowflake schema are ways to organize data marts or entire data warehouses using relational databases. Both of them use dimension tables to describe data aggregated in a fact table.
Databases are designed in different ways. Most of the time we can use “school examples”: normalize the database and everything will work just fine. But there are situations that will require another approach. We can remove references to gain more flexibility. But what if we have to improve performance when everything was done by the book? In that case, denormalization is a technique that we should consider. In this article, we’ll discuss the benefits and disadvantages of denormalization and what situations may warrant it.
A Unified View on Database Normal Forms: From the Boyce-Codd Normal Form to the Second Normal Form (2NF, 3NF, BCNF)
Normal forms for relations is a required topic of a database curriculum. Besides avoiding anomalies, which is already a big issue¹, knowing them certainly helps to understand what is going on in your or someone else’s database design. Even if at some point you decide to abandon a normal form, you should know what you are doing and how to pay a price for that. Here, I want to discuss normal forms up to Boyce-Codd Normal Form (that is 2NF, 3NF and BCNF).
The First Normal Form (1NF) is exceptional. The other normal forms (2NF, 3NF, BCNF) talk about functional dependencies and 1NF has nothing to do with functional dependencies. Moreover, we have precise definitions for other normal forms and there is no generally accepted definition of 1NF. Does 1NF Equate to “Atomic Attributes”? When you look at various descriptions of 1NF the word that you see most often is atomic. It is common to say that a relation is in 1NF if all its attributes are atomic.
When you read about normalization you usually get the set of conditions that a database in the nᵗʰ normal form should satisfy and the set of rules, a sort of a cook-book, for obtaining that normal form. But why these rules are safe to apply to your denormalized relations is a skip material. Here, I would like to present some elementary concepts on how we decompose relations and what can go wrong.
Why do you need all of this normalization stuff? The main goal is to avoid redundancy in your data. Redundancy can lead to various anomalies when you modify your data. Every fact should be stored only once and you should know where to look for each fact. The normalization process brings order to your filing cabinet. You decide to conform to certain rules where each fact is stored. Nowadays the go-to normal forms are either the Boyce-Codd normal form (BCNF), which we will cover here today, or the third normal form (3NF), which will be covered later.
Today we continue our series of posts on data normalization. In the previous post on data normalization I explained what functional dependency is. Today we will talk about candidate keys in a table. A candidate key is a set of columns such that all other columns in the table are dependent on it, and the set is minimal, that is if you remove a column, then the resulting set is not a candidate key.
Do you remember the post about update anomalies? I promised you we’d explain how to design tables which have no update anomalies. So here we go! Today we begin a series of posts on data normalization. We will talk about functional dependencies, a concept that needs to be explained before we dive deeply into database schema normalization. The subject is rather abstract and theoretical but I will try to restrain myself from going too deep into mathematics.
Let’s take a look at the following table: Customer Purchase date Product name Amount Price Total price Joe Smith 2014-02-14 Yoga mat 1 80 80 Jane Bauer 2014-02-16 Yoga block 2 30 60 Joe Smith 2014-02-14 Yoga block 2 30 60 Joe Smith 2014-02-14 Yoga strap 1 10 10 Thomas Apple 2014-02-18 Dumbbells 2kg 2 30 60 Jane Bauer 2014-02-16 Yoga mat 1 80 80 What’s wrong with this table?
A real-life example: Let’s assume that we have a system which stores data for distributors who sell products manufactured by some company. Each distributor receives points for selling products and may redeem a specified number of points to obtain a discount or extra bonus. Points are calculated by an external system and updated very frequently – after processing of each order placed by the distributor himself, a member of the distributor group, or a customer assigned to the distributor.