What are the most common database normalization levels?

The first normal form (1NF) is foundational for database normalization, ensuring data integrity by eliminating duplicate records. It's crucial to understand that 1NF is just the starting point for creating a well-structured database. By enforcing atomicity, 1NF eliminates repeating groups and arrays, which simplifies data manipulation and querying. However, while 1NF reduces redundancy, it does not address all forms of data dependencies, which is why further normalization forms are necessary to fully optimize database design.

First Normal Form (1NF) serves as the foundational step in database normalization, ensuring that each table adheres to certain rules to minimize redundancy and improve data integrity. By requiring the presence of a primary key for each table, 1NF enables unique identification of each record, facilitating efficient data retrieval and management. Additionally, the mandate for atomicity ensures that each attribute contains indivisible, single values, preventing data manipulation anomalies and enhancing database consistency. Embracing 1NF principles lays the groundwork for subsequent normalization stages, paving the way for a well-structured and robust database design.

Imagine a table in a database. First Normal Form (1NF) is like the first rule of organizing that table. It says: Each box (cell) should only hold one value. No lists or multiple entries allowed. No repeating groups of columns. Each column should represent a single piece of information, not several bundled together.

This might be controversial, handle with a grain of salt. Even if it is true that columns should not have multiple values in a single cell, sometimes it could be pretty useful approach. For example, Imagine a card game like poker. There are the tables card(card_id, color, number, shape), and game(game_id, ..., remaining_cards). The remaining_cards is an array of card_ids that are not drawn by the players. This is useful because when a new card is drawn, a procedure just get one register, the game, picks one card randomly and updates the same register.

The most common database normalization levels are: First Normal Form (1NF): Eliminates repeating groups and ensures atomicity. Second Normal Form (2NF): Ensures no partial dependencies by having a fully functional dependency on the primary key. Third Normal Form (3NF): No transitive dependencies exist; attributes depend only on the primary key. These levels help organize data efficiently, reducing redundancy & anomalies.

Second Normal Form (2NF) is super important in the world of databases because it helps get rid of redundant data by making sure that each non-key attribute relies completely on the primary key. To be in 2NF, a table has to pass some specific tests: - Every column should be directly linked to the primary key, not to other columns. - The table needs to already be in First Normal Form (1NF). - There can't be any partial dependencies, which means that no non-prime attribute (not part of any candidate key) can rely on just some of a candidate key. Tables should be organized so that all non-key attributes are fully reliant on the primary key to avoid any issues when manipulating data.

2NF ensures every piece of information, except the main identifier (like a customer ID), relies on the entire identifier, not just part of it. Think of it like a library book. The book's title (identifier) tells you everything about it, not just the author's name (partial identifier). This reduces data redundancy and helps avoid errors when updating information.

(2NF): A table is in 2NF if it meets the following criteria: It is in 1NF. Each non-key attribute is fully dependent on the primary key. This means that every non-key attribute must be determinable by the primary key alone, and not by any other non-key attribute.

3NF ensures each "folder" (data record) only holds information directly related to its unique label (the "key"). No information depends on other entries within the folder itself. This minimizes redundancy, preventing conflicting updates and making queries more efficient

Third Normal Form (3NF) is super important when designing a database schema. It basically helps cut down on repeating data, keep everything in order, and make managing data easier. To be in 3NF, a table has to follow these rules: - It's already in 2NF - None of the non-prime attributes depends on the primary key through another non-prime attribute An example of not meeting 3NF could be like in a hospital database where phone numbers are stored with patients, but they should actually be linked to doctors. This can lead to mistakes and double-ups. To fix this, tables need to be normalized to remove these dependencies. By sticking to 3NF, databases can stay organized, prevent repeat info, and keep everything running smoothly.

The Boyce-Codd normal form (BCNF) is a rigorous normalization technique building upon the third normal form (3NF). When a table harbors multiple candidate keys, BCNF ensures optimal data organization. Take an example of a table storing employee details, where both employee ID and department ID serve as candidate keys. BCNF mandates that every column in the table be functionally dependent on the entirety of every candidate key. This eliminates redundancy and ensures data integrity. To conform to BCNF, it's essential to decompose the table into smaller ones, each revolving around a single candidate key. This meticulous approach guarantees database efficiency and coherence.

The most organized way to store data in a database, preventing confusion and making it easier to find what you need. It ensures each folder only holds one specific type of information. No folder depends on another folder to be complete. This reduces redundancy and avoids conflicting information.

But why?? Normalization supports ACID: Atomization, Consistency, Isolation, and Durability. Normalization is about efficiently maintaining the integrity of the data in a transactional database system where complex changes to the data are anticipated, and where some transactions might need to be rolled back without affecting others. When your system makes a change to the database (a transaction), your system should touch only the tables and table rows that contain the data being changed. By normalizing data storage, closely related data elements are kept together, and unrelated or less related data elements are kept apart. How many degrees of normalization? It depends on the transactional model. Static data does not need normalization.