Get to know the most common database design mistakes
This post will give you a guide on how to make database design a little easier by highlighting some of the most general errors that developers make when they design the database.
Assuming that you know about database normalization and have a basic knowledge about relational databases, the following are just some of the common errors in database design that you can check when working with it-
• Browse and look for books by their titles, description, and writer information
• Comment on the books and give them ratings after reading
• Order the books
• View the status of order processing
This is known as design planning which works great for specific requirements. You need to set up a plan to know what the goal of the database is. When you have the outline of the project made beforehand, you can effectively build it correctly.
Experienced DBA professionals state that often this proper phase for planning is overlooked and ignored. The main goal for most developers is to get the job done. The project lacks direction, and it is obvious that problems are bound to arise in no time.
This is where the usual processing of making veiled promises start. The developers make a vow to go back and later fix these problems that never happen at all.
The solution to the above issue is to predict your project's needs and fulfill every issue that is likely to arise. You must mitigate these problems with careful planning as much as you can.
Experts from a credible company in database management administration and support, RemoteDBA.com, say data normalization has been around for about three decades. It is the fundamentals on which relational and SQL databases are incorporated. It can be said that SQL has been created to work with normalized data infrastructures. It does not refer to a plot by programmers of a database to annoy programmers of applications.
Note that SQL is quite addictive, and when you have the right data set out in place, you can build up results and values. For instance, you can use the FROM clause and take a data set and add or JOIN it to a new table. This means you can add several data sets together as you want to produce the final sets of data you need.
This addictive nature is vital as it makes the development process as well as the database performance easy. You must ensure that the forms are incorporated correctly so that you face no hassles with the database's performance and development. If needed, you should gather more knowledge on data normalization to obtain the desired results.
This post will give you a guide on how to make database design a little easier by highlighting some of the most general errors that developers make when they design the database.
Assuming that you know about database normalization and have a basic knowledge about relational databases, the following are just some of the common errors in database design that you can check when working with it-
1. Setting up the database model with planning-
One of the biggest mistakes you make with database design is poor design and planning. Assume you are about to design the database for a book store online. The system you design should allow the customers to perform the following activities-• Browse and look for books by their titles, description, and writer information
• Comment on the books and give them ratings after reading
• Order the books
• View the status of order processing
This is known as design planning which works great for specific requirements. You need to set up a plan to know what the goal of the database is. When you have the outline of the project made beforehand, you can effectively build it correctly.
Experienced DBA professionals state that often this proper phase for planning is overlooked and ignored. The main goal for most developers is to get the job done. The project lacks direction, and it is obvious that problems are bound to arise in no time.
This is where the usual processing of making veiled promises start. The developers make a vow to go back and later fix these problems that never happen at all.
The solution to the above issue is to predict your project's needs and fulfill every issue that is likely to arise. You must mitigate these problems with careful planning as much as you can.
2. Database normalization-
This refers to a set of techniques or methods to break down tables into constituent parts till each of them represents just a single thing. The columns should serve to completely describe the single thing that the table is made to represent.Experts from a credible company in database management administration and support, RemoteDBA.com, say data normalization has been around for about three decades. It is the fundamentals on which relational and SQL databases are incorporated. It can be said that SQL has been created to work with normalized data infrastructures. It does not refer to a plot by programmers of a database to annoy programmers of applications.
Note that SQL is quite addictive, and when you have the right data set out in place, you can build up results and values. For instance, you can use the FROM clause and take a data set and add or JOIN it to a new table. This means you can add several data sets together as you want to produce the final sets of data you need.
This addictive nature is vital as it makes the development process as well as the database performance easy. You must ensure that the forms are incorporated correctly so that you face no hassles with the database's performance and development. If needed, you should gather more knowledge on data normalization to obtain the desired results.
3. Insufficient testing-
Take this example- when your car indicates the engine has overheated, the first thing you blame is the engine. You hardly assume that something like the dial or, for that matter, anything else is broken for simply the following two reasons-• The engine is the crucial component of the vehicle, and it is common for you to blame this part of the system first.
• This assumption is often true.
As experienced DBAs know, the first thing to blame when the business system runs slow is its database. The reason is primarily because the database is the focal point of a business system. This is why frequent testing is needed of the database so that its limitations can be discovered.
Testing is a vital component of any database project planning; however, it is often overlooked when time slips. When there is a lack of sufficient testing, the functionality of the database suffers the most. End users will bear the brunt of malfunction like the "save" button not working and more. Businesses must get into deep system testing that ensures that it functions properly for the end-user. After all, developers and programmers have worked so hard. If you fail to conduct sufficient testing, the result will be bad for the business. End users will complain, and this will adversely affect the business to a large extent.
Again, you might believe that users have accepted your system as working, so will that not be good enough? Here, there is a problem with the statement. User acceptance is generally the standard that businesses accept when the end-user pokes around with the functionality slightly and gives a thumb up for the same. However, the user's acceptance is vague and should not be used as a testing standard.
The real test results are shown when users go deep down and test the production model. This is where performance-based issues are generally detected. Once they have been discovered, the next step is to get the proper performance tuning done for the database to function well without hassles to the end-user. Moreover, this testing should be done frequently over time so that issues can be detected early and arrested before they become massive.
• This assumption is often true.
As experienced DBAs know, the first thing to blame when the business system runs slow is its database. The reason is primarily because the database is the focal point of a business system. This is why frequent testing is needed of the database so that its limitations can be discovered.
Testing is a vital component of any database project planning; however, it is often overlooked when time slips. When there is a lack of sufficient testing, the functionality of the database suffers the most. End users will bear the brunt of malfunction like the "save" button not working and more. Businesses must get into deep system testing that ensures that it functions properly for the end-user. After all, developers and programmers have worked so hard. If you fail to conduct sufficient testing, the result will be bad for the business. End users will complain, and this will adversely affect the business to a large extent.
Again, you might believe that users have accepted your system as working, so will that not be good enough? Here, there is a problem with the statement. User acceptance is generally the standard that businesses accept when the end-user pokes around with the functionality slightly and gives a thumb up for the same. However, the user's acceptance is vague and should not be used as a testing standard.
The real test results are shown when users go deep down and test the production model. This is where performance-based issues are generally detected. Once they have been discovered, the next step is to get the proper performance tuning done for the database to function well without hassles to the end-user. Moreover, this testing should be done frequently over time so that issues can be detected early and arrested before they become massive.
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