7 Ways To Achieve A Shorter Database Design Process
A database is a structured collection of data, which typically maintains records on people or companies. Databases are organized so that they can be searched and sorted quickly to find the desired information. However, when it comes to database design, there's no such thing as "one-size-fits-all." Design a database that fits your specific needs by understanding the database design process and the best practices for executing that process.
What Is Database Design?
Database design is the process of designing, creating, implementing, and maintaining a database structure to store data. Database designers must be familiar with database best practices, which include choosing appropriate database types for different needs and making use of Database Design Frameworks (DDF). DDFs are essential because they provide quick and easy ways to enter data, saving database designers time in the long run.
Why Is Database Design Important?
In this day and age, businesses rely on their data to make better business decisions. They analyze their data to make more informed decisions regarding everything from their product development to their marketing and sales strategies. A well-designed database will not only store all of their data, but it will also organize that data so that it's easy to find and access whenever it's needed.
To ensure that the database is effective, you must implement a good database design. A poor design will make it difficult to maintain and update and can even harm the accuracy of your data.
Understanding The Timeline
Database design is a process. It's not something that can be done overnight-- database designers have to take care of all the details for a database to be successful and accurate. The timeline for a database design process varies based on several factors. Here’s an example of a typical database design timeline:
Analysis of Requirements
The first step of the database design process is to perform a requirement analysis. Such an analysis will allow you to identify what the database design will do for you and how it needs to be structured. You can break down this analysis into two parts:
When planning the database design, you will identify precisely why you need a database, whether the design process is feasible considering your resources (such as your development team, budget, and schedule), and whether the database will contribute to your company's objectives. Suppose the project is deemed both necessary and feasible. In that case, you'll begin collecting the requirements for the database by interviewing stakeholders and analyzing your organization's existing information systems strategy to determine what flaws need to be addressed (if any). Once you've completed the analysis, specify and validate the requirements in a document.
Defining The System
Once the planning stage is complete, define the scope of the proposed database.
Now it's time to start designing your database. Job one is to create a conceptual design, which involves specifying the proposed database's entities, columns, and their relationships. Using your conceptual design, you can create a logical model, which involves mapping the database model using the given requirements. Once the logical model is complete, you can create a physical model. The physical model involves defining your tables and how you will store your data in a DBMS (database management system).
Database Design Techniques
When it comes to designing your database, two main techniques are typically used. These include Normalization and Entity-Relationship (ER) Modeling. The normalization technique involves organizing your tables to decrease the redundancy and dependency of your data. This is done by dividing larger tables into smaller tables, linking them together via relationships.
Entity-Relationship modeling is a database design technique that defines the relationships between entities (e.g., people, places) in your database. ER modeling is typically done after normalization in the database design process to validate that your database will be normalized once it's been implemented in the database management system.
The very last stage of the database design is the implementation phase. Be sure your models are well-thought-out before you begin uploading data. If you have not thoroughly planned it out, your database may do a poor job collecting, storing, and organizing your data. Implementation involves two steps:
Data Conversion & Loading
Once you install your new DBMS (which can be done on an old server or a new server), you'll want to create the actual database using SQL (structured query language) and begin importing data into the database tables from your old systems. In some cases, your data will need to be converted to the proper format. Finally, segregate the data into tables and then change the data items into columns. At this point, you'll also need to determine how the tables are related.
- One-to-one: This relationship occurs when a record in table A is only related to one other record in table B. That other record is only related to one other record in table A, but it may not be the same record related to it. For instance, a specific security information record would only be related to one specific employee record.
- One-to-many: This relationship occurs when one record in table A may be related to numerous records in table B, but each record in table B can only be related to one other record in table A. For example, if a record of a company exists in table A and their full-time employees exist in table B. A company can have multiple employees, but those employees can only work for one company.
- Many-to-many: This relationship is when one record in column A can be related to many different records in column B. However, each of those records in column B may also be related to many different records in column A. For example, a customer may have bought many different types of products. Each one of those products may also have been purchased by many different customers.
Testing The Database
Once all the data is imported, and all the relationships are defined, it's time to test the database. During the testing, you'll check the created database against your requirement specifications and search for any errors that need to be fixed.
1. Get The Fundamentals Right
A database design process can be a long, drawn-out endeavor if you don't start with the basics from the get-go. The following are the fundamentals that you need to get right to ensure that you're not only able to create and implement a successful database design but that you'll be able to achieve it in a shorter timeline as well:
- Model documenting: The modeling phase is where you'll decide what data items will be collected, stored, and organized. Documenting these data items and their attributes is a crucial step to database design because this will help you to identify the database's requirements and then create its models.
- Indexing: Indexing is a process of organizing and storing information about specific columns to be found more easily. When you index data in a database, it's not actually adding data to the database. However, it does help to make database design faster and more efficient.
- Watching the keys: Watching database keys is the process of monitoring and rechecking database tables to make sure that they are correctly constructed and in the correct order.
- Avoiding nulls: Database nulls occur when you store data in a database for any column that does not have values. Avoiding nulls will help to reduce database clutter and improve database performance.
- Following conventions: Conventions in database design are standards that have been established for the database's layout, including data types and naming conventions. By following conventions, you'll not only have a database that is easier to read and understand, but you'll also be able to find data more quickly.
- Implementing integrity checks: Implementing database integrity checks is the process of verifying that data has not been changed or deleted.
2. Document Your Database Design
Creating database diagrams can help you to design your database in a more precise and structured way. To document the database, create an ER diagram for each table. An ER Diagram is used as documentation of how data flows within a database system. It also outlines how tables are related (One-to-one, One-to-many, Many-to-many), database constraints (Primary keys, Foreign Keys), and database design elements.
3. Define and Label Tables and Columns Consistently
Each database table should have a title, and each column within that database table should be labeled. The label for the database columns can include information about what kind of data is in it or how to use this field (i.e., primary key). These labels must be consistent across database tables so that you know what database column contains what kind of data.
4. Normalization Is Vital
The normalization process involves splitting database tables into smaller ones so that each table has no more than one subject per row (known as first normal form) or removing columns from database tables so that there are only two fields in the database table - which guarantees third normal form. Normalization helps achieve a shorter database design process because it ensures that your database is accurate, secure, and organized.
5. Take Advantage Of Stored Procedures
Stored procedures are database objects that allow you to store database definitions, formatting, and other general database maintenance. You can also use stored procedures to create database triggers, which are set to automatically update database records that have been inserted or modified. Stored procedures will shorten the design process by eliminating the need to repeat database maintenance tasks.
6. Automate Your Pipeline
The database design process can be made shorter by automating your database pipeline. The database can be designed to automatically create, update and delete data as necessary based on user input or database triggers (i.e., inserted records). Without this automation in place, you'll have to code each database table entry manually, making for a lengthy database design process.
7. Test Your Design Prior To Releasing It
Testing database design functionality helps to make your database more efficient and reliable. To do this, create a test database of the same size as your production database. After you've built the test database, simulate all possible scenarios that may happen with it (e.g., insert data). If any problems occur while testing, then they can be fixed or corrected. Proper testing can save you a significant amount of time fixing minor issues that develop into enormous headaches further down the road.
Implement The Best Practices To Minimize Delays
As you can see, database design is a complex process that requires careful consideration. The best way to shorten this process is by following database development best practices, implementing database integrity checks, and ensuring that your database is well-documented. Of course, unforeseeable issues and delays can still occur, no matter how much time and effort you've put into each step of the process. Don't let such setbacks discourage you. As long as you understand the fundamentals of database design, you'll be on the right track.