A database includes bulk information deposited in a framework, making it easier to locate and explore relevant information. A well-designed database contains accurate and up-to-date information, allowing and data to be fetched easily whenever needed.
In this article, we’ll discuss the importance of a good database design and how it can benefit your data endeavors. We’ll also go through some of the most common database design techniques. Lastly, we’ll cover basic steps and best practices to help you design a good database for your organization.
What is a Good Database Design?
A good database design process is governed by specific rules. The first rule dictates that redundant data must be avoided; as it wastes space and increases the probability of faults and discrepancies within the database. The next rule is that the accuracy and comprehensiveness of information is extremely imperative. If the database contains erroneous information, any documents that fetch data from such a database will also include inaccurate information. Consequently, any decisions based on those documents will be misleading.
So, how can you ensure that your database design is good? A well-designed database is the one that:
- Distributes your data into tables based on specific subject areas to decrease data redundancy
- Delivers database the information needed to link the data in the tables
- Provides support, and guarantees the precision and reliability of data
- Caters to your information processing and reporting requirements
- Functions interactively with the database operators as much as possible
Importance of Database Design
Database design defines the database structure used for planning, storing, and managing information. Accuracy in data can only be accomplished if a database is designed to store only valuable and necessary information.
A well-designed database is imperative in guaranteeing information consistency, eliminating redundant data, efficiently executing queries, and improving the performance of the database. Meticulously designing a database saves you from wasting time and getting frustrated during the database development phase. A good database design also allows you to easily access and retrieve data whenever needed.
The reliability of data depends on the table structure; whereas creating primary and unique keys guarantees uniformity in the stored information. Data replication can be avoided by forming a table of probable values and using a key to denote the value. So, whenever the value changes, the alteration happens only once in the main table.
As the general performance of a database depends on its design, a good database design uses simple queries and faster implementation. It is easy to maintain and update; whereas fixing trivial interruptions in a poor database design may harm stored events, views, and utilities.
Database Designing Techniques
The two most common techniques used to design a database include:
- Normalization: Tables are organized in such a way that it decreases data redundancy and dependency. Larger tables are divided into smaller tables and are linked together using relationships.
- Entity-Relationship (ER) Modeling: It’s a graphical database design approach that models entities, their attributes, and defines relationships among these entities to signify real-life objects. An entity is any real-world item that’s different or unique from the surroundings.
Steps to Design a Database
Database designing generally starts with identifying the purpose of your database. The relevant data is then collected and organized into tables. Next, you specify the primary keys and analyze relationships between different tables. After refining the tables, the last step is to apply normalization rules for table standardization.
Let’s look at these steps in detail:
Define the objective of your database
The first step is to determine the purpose of your database. For example, if you are a small home-based business, you could be designing a customer database that maintains a list of consumer info to generate emails and reports.
At the end of this step, you’ll have a strong mission statement that you can refer to throughout the database design process. It’ll help you concentrate on your objectives when making important decisions.
Locate and consolidate the necessary data
The next step is to collect all kinds of information that you might want to store in the database. Begin with the current information. Mull over the questions you want your database to answer, and it’ll help you decide which data needs to be recorded.
Distribute the data into tables
Once you’ve amassed all the necessary data items, the next step is to divide them into main entities or subject areas. For example, if you are a retailer, some of your main entities could be products, customers, suppliers, and orders. Each entity will then become a separate table.
Here’s an example of how you can divide data into different entities:
Change data items into columns
Data is segregated into tables, such that every data item becomes a field and is shown as a column. For instance, a Customer table might include fields like name, address, e-mail address, and city.
After determining the preliminary set of columns for every table, you can refine them. For instance, customer name can be recorded as two distinct columns: first name and last name. Likewise, you can store the address in five distinct columns based on address, town, state, zip code, and region. This will make it convenient for you to filter information.
Identify primary keys
The next step is to select a primary key for every table. This primary key is a column or a set of column that’s used to distinctively pinpoint each row. For instance, in your customer table, the primary key could be customer ID.
More than one primary key can also exist, called a composite key, including multiple columns. For example, in your Order Details table, primary keys could be order ID and product ID.
Determine how tables are related
After dividing data into tables, information needs to be brought together in a meaningful manner. So, explore each table and determine how the data in one table is linked with the data in another table. If needed, you can add fields or form new tables to simplify the relationship.
Below is an example of different entity types and relationship types.
In this step, you’ll create one-to-one, one-to-many, and/or many-to-many relationships between different table entries.
When only one item from a table is associated with an item from another table, it’s called a one-to-one (1:1) relationship. In a one-to-many (1:M) relationship, an item in one table is related to many items in the other table, such as one customer placing several orders. A many-to-many (M:N) relationship occurs if many items from one table are related to many items in other tables.
Enhance your database design
Now that you have all the required tables, fields, and relationships, the next step is to refine your database design by creating and populating your tables with mockup information. Experiment with the sample data by creating queries or adding new items. This will help you analyze your design for faults and you’ll be able to highlight possible errors. If needed, adjust your design to mitigate those problems.
Implement the normalization rules
The last step is to implement the normalization rules for your database design. It is a systematic approach that removes redundancy and unwanted characteristics, such as Insertion, Update, and Deletion irregularities.
This multi-step process stores data in a tabular form, eliminating redundant data from the relation tables.
Final Words
The database design process helps you simplify the design, development, execution, and maintenance of your corporate data management system.
A good database design can help save disk storage space by reducing data redundancy. Along with maintaining data precision and reliability, it allows you to access data in various ways. Moreover, a well-designed database is easier to use and maintain.
Originally published at https://www.astera.com on October 1, 2019.
