Whether you work on a corporate database that consists of hundreds of records containing millions of valuable data pieces, a proper database design is a crucial task. A good database structure will make the storage and retrieval of data easier, but it can also simplify the database’s scaling in the future and ensure security. However, it is also very easy to fall into the traps of poor database design practices, making things difficult and challenging for you in the future.
There are many articles and books written on the topic of database normalization. Still, on the other hand, if you avoid the simplest and most common mistakes in database design, as we discuss here, you can be on the right track in terms of an ideal database design. You may be a pro or just a beginner in database development. In any case, knowing these most common mistakes, database designers tend to make will be of help to you to keep away from those. There are many shortcuts suggested by techies, but it not the shortcuts but the thorough fundamental knowledge of the best practices and possible mistakes that make you a pro.
Even though it is acceptable to take chances while you design databases, you can also take concrete actions to ensure a foolproof approach. Here, we discuss some fundamental tips to avoid the most common database development mistakes people tend to make. These may help save you time and effort ton the long run.
Avoiding the most common database mistakes
Common DB design mistake #1: Weak naming standards
Let us start with the simplest errors, but the most obvious, the naming standards. Even though it is quite simple for anyone to understand that poor naming structure will cause many issues on the go, most of them still do not stick to any standards, at least not every time. Naming standards can be a personal choice, but one should ensure that the choices made are relevant, consistent, logical, and properly documented for future reference. Here are some standards to follow:
- Consistent: For example, if you are considering the address field for customer address, then you need to follow a standard naming than representing it in many ways, i.e., custadrs or customeradress, etc. Choose the simplest and easily understandable name, document it, and stick to it.
- Logical: If the naming standards you choose are documented in full, there may be hundreds of pages out there. Even though it is important to document the same, no one may want to go through all these each time they come across a name. So, ensure that your names are relevant to the fields they represent. Say, for example, the date column name may end with _date tag. Future users should be able to figure out your logic easily and follow it.
Common DB design mistake #2: Misuse of Primary Key
It is also very common that many do not know the proper use of the primary key; many forget it. Here are some things to always remember.
- You should not base the primary key value on data in the given row.
- This value should not have a meaning, and so the application data is not properly.
- The system randomly or sequentially generates these values.
- Primary key values may not ever change.
The primary keys need to have all these properties. So you can move the data from one system to another and change the underlying data without any complicated or contradictory relationships. For fine database tuning, you may also take the assistance of expert providers like RemoteDBA.com.
Common DB design mistake #3: Repeating the fields in tables
One of the fundamental principles of an ideal database design is to recognize the repeating data and put the repeating columns in the respective tables. Repetition of fields in a table is a common mistake done by those who are used to spreadsheets. While the spreadsheets are very flat, databases need to be in a relational structure. Spreadsheet to the database is similar to a transition from 2D to 3D.
However, once you know it, It is very easy to spot the repetitive fields and restructure. Make sure that each table you crate holds its unique ID. This acts as the primary key, and in turn, we can link the tables by assigning these primary key values as the foreign key in other tables.
Common DB design mistake #4: Poor documentation
This is a no-brainer, but in fact, many tend to ignore the importance of it. You need to specify all the naming standards followed, table definitions, relationships, and the documentation columns, which can be easily accessed and understood by the users and programmers in the future.
However, it is not just enough to have documentation with the definitions and names alone, but you need to specify how you expect this database structure to be used. Even though it may take time, it is ideal to have all your bases covered than to wait for a collapse with a rebuilding need.
Common DB design mistake #4: Overusing the stored procedures
You need to check out how often you tend to use the stored procedures. In standard cases, it is being used a lot. There are certain times when you must be using them; however, relying too heavily on it may cause some issues. Say, for example, if you want to update a stored procedure by making some changes to it, you must write a fully new stored procedure most of the time. This is because you do not know which systems are currently running with that stored procedure. Having multiple versions, it becomes really hard to understand the versions specifically. To prevent such stored procedures related to confusion, it is best to use the advanced ORMs. Following this will make the process much more efficient.
Also read: 2021 Data Governance and Choice of SQL vs. NoSQL as Enterprise Database
Some other common mistakes to keep an eye on are improper normalization of the DB, inappropriate index usage, following hard deletes, and incorrect usage of Exclusive Arcs, etc., which you should avoid.
