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Seven Mistakes to Avoid While Designing Database Systems

Database designs put logical models into practice with the help of the relational database. Most of us are aware of low-quality designs’ harms but do not know how to correct them. However, ignoring them can play havoc in the long run. Some of them are so simple to overcome that you need extra attention to the perfect design. The silly, unattended mistakes will ultimately question your professionalism and skills.

Most of the beginners are more enthusiastic about intricate coding than a good data model. Perfect design makes use of one’s intuitions, aesthetics, and subjective bias of its designer.

I have been going through several database designs lately and found some common mistakes in most of them. Here I will try to explain the seven most common errors in any database design and how you can avoid them for some flawless, highly professional results.


To make your data more presentable, you need to check the column size and adjust it for each data type. For example, some data types, e.g., a number, do not need wide columns to continue. In the same way, a comment or notes section needs wider columns. A mistake most of the database designers do not focus on is using the precise size of columns. You have a wide limit to adjust between, and you have to use it smartly to make the design more aesthetic and presentable. A right column size can also facilitate you with data transfer to another system easily. For example, go for the VARCHAR2 column having a person’s name only. You will be in great trouble because your data warehouse and all of the procedural steps should also allow the use of this much length (4000 characters).


The database offers multiple features that most of us ignore. It not only makes the job challenging but also less efficient.
Some of these features are:

• Use of check constraints virtually to reinforce the value
• Use of sequence aiming to generate the primary key.
• Use of privileges and user role to reinforce access.

Moreover, you can also manage massive data using IaaS as a primary computing medium. Modern techniques and tools provide modified efficacy and speed. Using various additional database management tools, for example, MySQL IDE and similar ones, also helps a lot to optimize your work. Thus, companies tend to prefer employees with updated skills and hire them on priority.


Normalization transfer random ideas into orderly columns and tables in database design. Then, it tends to follow destined rules to prove their efficiency. Everyone out there does normalization differently, and it’s specific to every developer. However, you have to follow different rules to have a well-formed database; otherwise, you will end up with lots of redundancies and deleting important data. Your database must be at least a third standard. If that’s not the case, look into spending time upgrading your design.


We design indexing on a database to run queries using a smart approach. However, they are not master keys and solve every issue. While indexing developers either do not create indexes or create too many on every field.

Both of the cases mirror the unprofessionalism of any developer. Using no indexes is like missing a golden opportunity. Moreover, too many can also play havoc. Indexes do help in comprehending data properly. However, too many can make the whole system process too slow to function correctly. Always aim for a middle ground and be smart in indexing. It can prove a total game-changer.


While developing a database, the developer tends to determine a type of data for each column. He has to pick between date, text, and number usually. It only comes with experience and increases the worth of any developer. For example, you always think of using numeric data for adding account numbers. However, more smartly, you can use character values too!

The type of data you are using can immensely affect its proper storage and retrieval later.


Data storage is adequate inside a database, but it can also become complicated for many.

You can always store some date-time or date data in your database. That’s simple when it comes to necessary information like birthdates. However, for log files, you can use the feature to get precision up to fractional seconds. In doing so, you need to be very efficient with the type of data. Moreover, how much accuracy and efficacy your database offers in different time zones.


Documentation is compulsory when you want to access the data in the future. Many of us find difficulty tracking and understanding the relationship between multiple tables, whole reading the data after a while. If you want to prevent this, make an ERD of your entire database and try to keep it up to date. It will help you every time you look at your database to upgrade it. Thanks me later!


Designing a database can make it super easy to store any data. However, it can become tricky sometimes. The better presentation and readability of the data is an unsaid slogan of your proficiency. Many beginners and many times, professional developers fail to produce an excellent database design. After years of experience and thoroughly looking into most models, we have worked into the most common mistakes developers make. Try to avoid these and go for smarter approaches to get a flawless database that will prove its efficacy for a long time.