Database design is the process of building an application, as a database is simply information that’s stored in a searchable framework. The design aspect involves the rest of the details. Learn how you can use the top # database design best practices to create a beneficial final product. Without them, you will produce a product with poor planning and performance after production.
What Are Database Design Best Practices?
To explore what makes food database architecture and the concepts that go with database design, we must understand the fundamental design principles behind useful databases. A good database (and what constitutes the best practices for a valuable final product) can be broken down into six primary objectives, according to Lazy Heap:
- Data Integrity
These factors ensure the database is designed in a way that makes it useable over a long period, extending into and anticipating ever-changing technology. It needs to be adaptable, offer enough integrity to keep information safe, and perform well.
While designing a database system, keep the following best practices in mind:
Consider All Viewpoints
When you’re in the planning stages, make sure to build a database design that matches up to expectations. Get input from your project sponsor, including the stakeholders in the product, and ensure you can reach their expectations as well. Consider how long it may take to train users to use any search functions and keep the organization simple. The first step to make this happen is to sit down with your organization and decide on a format of data and how it can be meaningfully represented.
Select A Type Of Database
Find the type of database right for your project and select the right tools for your needs. For many people, this decision is as easy as selecting either SQL or NoSQL, but there are other more specific types of databases that are more appropriate for certain projects as well. You’ll need to decide which type of database is best for what you’re designing right off the bat.
To decipher between the two main database types, think about your needs. Databases known as SQL are considered the standard in structured data, especially if integrity is vital. However, new technology such as the Internet of Things (IoT) or machine learning requires fluidity, scalability, and fast speeds. These requirements make NoSQL the best option, which is why this framework is commonly used in social networks, web analytics, and even other database types as well.
Depending on the type of database you’re working on, you may use a different modeling technique. Online transaction processing databases, for example, require the use of transactional modeling. Relational databases, on the other hand, will do better with a dimensional form of modeling.
Many online tools are available when it comes to building a database or application, and options such as Draw.io, Lucidchart, or Microsoft Visio each supported database entity design. Use the wrong data type, however, and you can face many negative consequences such as bloated files, inaccurate data, and difficulties when it comes to syncing attributes or joining tables.
Normalize the Data
Many of today’s companies function on a blend of the two most common types of databases: SQL and NoSQL. They can work together to create intricate designs, and these complicated structures need to offer minimum redundancy by normalizing the data. To get started, you’ll want to eliminate any multi-valued or repeated attributes before starting on subkeys.
Create Transparent Structures
Keep in mind that what you’re creating is as much for future users as it is for you, your team, or your organization. Design the database with the future at the forefront of your mind, as people may later need to modify, add, or change something to keep the database up with current technology trends. Don’t try to reinvent the wheel, just keep the design simple. Everything changes eventually.
Avoid shortcuts, plurals, or abbreviations. Make sure you maintain consistent naming and stick with the convention you set out. Most designers will even create a key or style guide to help the entire team stay current with the design practices and structures you present. Style guides lay out the guidelines for all tables, foreign keys, indexes, triggers, and other functions.
No matter what naming convention you select, stick with it. Choosing something is better than offering no set standard, and you can (and should) use the rules that are already in place in your industry rather than trying to change the way things are done.
On that note, communication within your team is also vital to spot shortfalls and improvements before it’s too late. With the entire team on the same page and consistent use of guidelines everyone knows and understands, you may spend more energy, time, and money fixing mistakes.
Define Any Constraints
By defining the constraints of your design, you can maintain the utmost data integrity. Check out the full range of options, like check or foreign key, and stick with business rules along the way. Doing so will ensure the application can prevent some of the harmful data from entering the system. Create an outline with all the database’s requirements and clearly outline the software’s future as you see it now. Plot out everything you can, but don’t forget to pencil in time for flexibility or problem-solving.
When defining, try using small values as well. This can help boost performance because smaller amounts for each set of data is easier and faster to locate. Large binary data sets should be stored somewhere other than the tables as well, which also improves performance by simplifying the process.
Document It All
Document everything about your design, especially your primary keys, entity-relationship schemas, and the triggers future users may need. As before mentioned, having a guide or key will keep the whole team on track and documentation can help you achieve this. It may seem like an unimportant, busy task; however, documentation is essential to the design process.
Give meaningful and useful names that are descriptive for your team and for future workers who may alter your product later. Properly documented conventions will help maintain the product over time and reduce the number of errors that can take place out of confusion or misinterpretation. Whatever you do, stay consistent in your choices as well.
Plan For Backup Time During The Build
By planning, you can add in time to handle any issue or disaster that comes your way. Problems will come up. It’s only a matter of time. Plan out what will and could happen before you dive too deep into the design process. Pencil time into your schedule for automatic backups, failover clustering, replication, or anything else you find necessary to keep your database’s structure in perfect shape.
This tip can save you so much time during the development process. Rather than needing to repair issues as they come up or hoping everything will work when the product hits production, your team can instead prevent problems from happening in the first place.
Information is valuable and can become destructive in the wrong hands, so it’s vital to maintain privacy and security. Today’s people value privacy, which is a growing concern in the age of technology. The information on your database needs to be stored and organized securely, so use encrypted passwords and never assign an administrator who doesn’t have the right privacy training or verifiable qualifications. Also, you’ll want to close the database as soon as you can to avoid threats. If there’s any vulnerability in your design, you could face issues that impact the entire enterprise.
Optimize The Speed
Fast databases are ideal, so consider using tools in your design such as Elastisearch to help improve your search speed rate. You’ll also want to speed up the process by making an index for your regular search queries. An analyzer can help you figure out if you need a clustered index or traditional index for your project.
Allow The Database To Function On Its Own Server
Lower your CPU usage by placing the database on its own server, not the server you use for the web. This will free up some computation resources, allowing you to keep the database away from the hands of unauthorized users as well.
Why Are Database Design Best Practices Useful For Your Final Product?
If you don’t use these database design best practices, you won’t create a useful final product. It’s that simple. With the right database design, the development and following deployment of your product will perform well after the production stage.
Well-designed databases work well and give people little trouble later. They are tested to ensure they deliver the right end-user experience you’re going for with the developed system. Use the best practices if you want smooth sailing. Otherwise, the process could be a huge, expensive mess for your entire team. Serious mistakes can cost you.
How To Use Database Design Best Practices
Databases and their frameworks change over time, the same way a business isn’t set in stone. Workflows and frameworks may change and using these database design best practices may ensure your product sticks around longer. Always begin by thinking about the bigger picture and considering the future of technology, the world, and how all these factors may affect your product later.
Top Mistakes In Database Design To Avoid
Common mistakes happen in any industry. Here are the worst mistakes you could make in database design, which often takes place if you fail to follow the design best practices:
- Poor development and design mapping during the planning process.
- Leaving inconsistencies between each environment in the database.
- Not communicating with other team members, DBAs, developers, or higher-ups.
- Disregarding how your product will function with other apps and their restrictions.
- Completing checks and reviews way too late or after the product hits production.
- Using poor naming standards and codes, or not using them consistently enough.
- Using a single table to house all the domain values.
- Using redundant tables and fields.
- Only using a guide column or identity for your main key.
- Not planning for the future.
- Not accessing data through stored procedures.
- Ignoring the data’s real purpose.
- Incrementing poor normalization principles.
- Not properly indexing information or processes and using poor names.
As with planning out anything else huge in life, being prepared is the best way to create a lasting product. Always be prepared for anything that can happen and consider how future changes can impact your work. For a more detailed list of exactly what to do, DZone’s 20 best practice tips are a great place to start. This forum on Stack Overflow may also be useful to you.