Databases are the fundamental components of enterprise applications and computer systems. They store and share the relevant data required to run software applications, the information sought by the customers, and data for business analytics, etc. A database is always up and running in the background, and in some cases, there may be multiple databases at work to ensure that the applications are functional. You may think of a database as an information warehouse where tons of information will be stored in a structured manner to make it easily searchable and accessible.
This makes database design a crucial step in building any software or enterprise app, where the developers need to design an efficient and capable database. Let us explore why database design atters in successful enterprise functioning and what a good database design means?
Why is DB design important?
You may consider an online clothing store as an example where the website is the storefront from which customers buy things. The process of buying an attire from this e-com portal may seem simple, but there is a good deal of information exchange at the backend. When you initially browse the website, it will show you a custom list of categories and available products under each. You can also see the price, available colors, sizes, and other related information about the product here.
All these data, which this website retrieves, is coming from the database where the information is stored. When you choose a particular item and opt to purchase it, the website will ask for the personal details, address for shipping, billing address, payment details, order confirmation, etc. These new data produced during this process also goes into the same database and stored there.
Database design is a crucial aspect of these entire operations. A good database acts as the backbone of any software application, which is scalable and can handle high workloads. To work effectively on database design, then it is crucial to choose an ideal database software. There are many databases available out there, which you can choose to pair with your application. You may choose from free databases to premium ones and also among relational, non-relational database software out there. Once choosing the right one, the next step is to design it to meet your exact requirements, and here are some design best practices to follow.
Database design best practices
1. Take every perspective into consideration
To design a good database, you must keep in mind every perspective of the different stakeholders. Try to gather as much input as possible and understand what they expect from an ideal database. You may also consider their skillfulness in working with database technologies. Doing this fundamental evaluation will help you get a clear idea about how technical the database you design should be and how to train the users on its features.You may also take the support of reliable service providers like RemoteDBA.com for data design consulting.
2. Select a proper database type
There are different types of databases available. So, choosing the right type of database is a critical part of DBMS design. You can primarily categorize types of databases in two ways as
- Based on the query language of the database for data manipulation. Databases that use SQL are the most popular model. In contrast, there are NoSQL databases, which are now largely used for data mining, machine learning, analytics, the Internet of Things, etc. Compared to SQL DBs, NoSQL databases feature more flexibility, scalability, and speed.
- Another way to categorize databases is based on various data models. In light of this, there are four types of database as relational DBs, hierarchical DBs, network DBs, and object-oriented DBs.
It is the most fundamental step to do thorough research on different types of DBs available and choose the right type to fit your enterprise application needs.
3. Define tables and columns
You need to define the data items and label the columns and tables. For this, it is important to have a consistent plan for the same. You may consider giving the simplest names to the tables to define the data it contains. For example, ‘CustomerName’ can be the name of the column consistent with the customers’ names.
Normalization of a database stands for organizing all information within the given database to avoid redundancy or replication. Normalization is the processing of the data further into smaller relational tables instead of storing it in one big table. This is an ideal database design practice to ensure data efficiency. However, you need to ensure no scope of over-normalization, too, as it may further distribute the data into smaller tables, which makes things more confusing.
5. Documenting database design
It is also important to do proper documentation of database design. With proper documentation, database developers and administrators will keep track of all the details related to it. The database design should also be documented with supporting instructions, diagrams, stored procedures, etc. Ensure this documentation provides enough info to the programmers, admins, end-users, and other stakeholders on how to use and update it.
6. Maintaining privacy and security
Many times, information in databases may be confidential where privacy is a major concern. To ensure optimum security, you must encrypt the passwords, restrict the database access, have strict authentication, and use separate servers for your applications and database storage. Adopting these measures will ensure that your data is secure from any attack and does not breach the privacy settings.
As we have seen here, the ideal database design now is a scalable one and should handle higher workloads expected in the future. For businesses that plan to grow, it is important to consider while designing a DB. Also, keep a common mistake during database design as not using stored procedures. These are prepared codes that will be handy when you need to manipulate the data. If an SQL query which you see often, it will make your task easier to code that query in a stored procedure than writing it again and again.
Considering all these factors, you need to spend time effectively modeling and designing your enterprise databases to get the most out of them.
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