How can you use entity-relationship modeling to normalize a database?

1 What is entity-relationship modeling?

Entity-relationship modeling (ER modeling) is a technique to represent the data structure and the logical connections between different data elements in a graphical form. An ER model consists of three main components: entities, attributes, and relationships. Entities are the objects or concepts that you want to store data about, such as customers, products, or orders. Attributes are the properties or characteristics of each entity, such as name, price, or quantity. Relationships are the associations or interactions between entities, such as one-to-many, many-to-many, or one-to-one. For example, a customer can place many orders, but an order can belong to only one customer.

2 How to identify entities, attributes, and relationships?

To identify the entities, attributes, and relationships in your data, you can begin by considering the purpose of your database and the questions you want to answer. This helps to identify the main nouns which are likely to be your entities, as well as the adjectives or modifiers that describe them – these are likely to be your attributes. Additionally, you can discover relationships by recognizing the main verbs that connect your entities. Finally, drawing an ER diagram that uses symbols and notation – such as rectangles for entities, ovals for attributes, and diamonds for relationships – is a great way to visualize your data.

3 How to apply the levels of normalization?

To apply the levels of normalization to your database, you can use the ER model as a reference and follow certain rules. First normal form (1NF) requires eliminating any repeating groups or arrays of data within an entity. Each attribute should have a single value for each entity instance. Second normal form (2NF) eliminates any partial dependencies, meaning an attribute depends on only part of the primary key of an entity. Third normal form (3NF) eliminates any transitive dependencies, meaning an attribute depends on another attribute that is not part of the primary key of an entity. For example, if you have an entity called customer with an attribute called address that depends on another attribute called zip_code, you should move it to a separate entity called address and link it with a relationship. Following these rules will help ensure your database is properly normalized.

4 How to check the quality of your normalized database?

To assess the quality of your normalized database, you can evaluate it against criteria such as data redundancy, data integrity, and data flexibility. Data redundancy should be minimal or nonexistent, with each piece of data stored in one place and referenced elsewhere as needed. Data integrity should be ensured to guarantee accuracy and consistency; each entity should have a unique identity and each relationship should have an appropriate cardinality. Lastly, the database should have the capability to accommodate changes in data requirements without affecting the existing structure or functionality; users should be able to add, modify, or delete data without impacting other elements.

5 How to use entity-relationship modeling in practice?

Entity-relationship modeling is a useful tool to help you normalize your database, but it is not the only one. You should also consider other factors, such as the performance, security, and usability of your database, when designing it. You should also test your database with real or simulated data and queries to evaluate its efficiency and effectiveness. You should also document your database design and update it as needed to reflect any changes or improvements. Entity-relationship modeling is not a one-time process, but an ongoing one that requires constant review and refinement.

6 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?