A Guide to Designing Enterprise Database Schema


Olivia JensenBusiness Advisor

Monday, April 5, 2021

Designing database schema is an advanced strategy for making a perfect framework for effective data management. As in the case of architecture, a strong database must have an excellent blueprint to keep the project on the right track.

Article 5 Minutes
A Guide to Designing Enterprise Database Schema
  • Home
  • IT
  • Storage
  • A Guide to Designing Enterprise Database Schema

A database schema will act as the blueprint for setting up a database with huge data. An ideal database schema forms a skeleton structure that represents the logical view of a database. By defining the data categories and their relations, a schema design ensures that the data is made easier to gather and interpret. This article will provide an overview of database schema design and list examples of best practices in schema designs aimed at database optimization.

The relevance of database schema design

The enterprise database stores all crucial data needed for business operations to run their systems and software applications. For every organization, there may be at least one database on all the time to keep applications running. However, there’s no point in having random data in a database without having the ability to analyze it. Data organized inefficiently on a database will eat up your time and effort and may ultimately leave you in chaos. This is the reason why database schema is important.

A schema design will help organize the data going into your enterprise database into different entities. This will help you determine how to establish logical relationships between these and what constraints to be applied to the data. Database designers create schemas to give the administrators and analysts a logical insight into the data and make it easier to store, manipulate, retrieve and produce reports.

How does a database schema exist?

The design of a database schema may exist either in a set of formulas or visual representations. It may use some constraints, too, which govern the database. The developers and database admins may express these formulas in a different set of data definitions based on the nature of the database system they deal with. Even though various database systems in use now have different definitions in terms of the schemas, some top databases like Oracle, MySQL and SQL Server support the standard CREATE SCHEMA statement.

For example, imagine creating a standard database schema for various departments. The analysts in different departments may have access to the schema account of their particular department. Say the financial analyst creates the views and tables in the finance schema. This analyst will also offer access to the other team members to read the tables listing Employee IDs, incurred expenses over a period, etc. Another standard table may be that of employee salaries. With these, analysts will be able to determine which users may write, read or edit the specified datasets.

Elements of database schema designs

The database schemas can be divided into two major categories:

  • Physical DB schema: As the name suggests, this refers to how the data gets stored on a physical storage system in different forms as indices, files, etc. It also indicates how you can store the data later in the database. The physical schema will help admins arrange the data logically on defining its attributes.
  • Logical DB schema: Logical schema will incorporate all logical constraints applicable to the data, and it defines the tables, fields, views, relations and integrity constraints. This offers all the required information that programmers and administrators can apply to the database's actual physical design. The physical tables in the database schema come from the logical model. Entities further become database tables and the attributes, in turn, become the fields in the table.

Considering the above finance example, the specific database schema may have a two-table structure:

  • In table #1, the title is 'Users,' and the fields may be 'ID, Name, Mail ID, Date of Birth, Department' etc.
  • In table #2, the title might be 'payment,' and fields are like 'ID, Name, time worked, billed hours,' etc.

There are a few information pieces in the single schema, which include titles of the Table Names and the Fields in each table and the relationships between these tables. The developers may convert these into SQL codes for the physical database.

Schema design best practices

To get the most out of schema design, follow these best practices to make sure that developers have a definitive reference about the database tables and fields:

  • Use proper and easily understandable naming conventions to make the design schemas effective
  • When you decide on a particular style or try to stick to ISO standards, always be consistent in the name fields
  • Don’t use the reserved words in table names for SQL Server DB, for example fields or column names, as these may end up in syntax error while running
  • Avoid quotes, hyphens, special characters and spaces in between, while putting names as these may not be valid
  • Always use singular table names like CustomerName or BillNumber etc., vs. CustomerNames or BillNumbers. As the table denotes a collection of entries, there’s no need to name it in plural
  • Avoid any irrelevant prefixes or suffixes in the table names. For example, use Department instead of DepartmentList
  • Document the design schema and instructions for a better understanding of the same later and write comments for triggers and scripts
  • You can use normalization as needed for optimizing the performance. Under-normalization and over-normalization may however result in impaired performance
  • To ensure security, always keep the passwords encrypted, don’t provide admin privileges to all users and enable authentication for accessing the database

Understanding your data and the various attributes of each element in it will help you to devise the best schema design for your proposed database. A well-prepared schema will help your data grow in a controlled manner. Even when your data keeps expanding, you can easily analyze each field with properly mapped relation with one another as specified in your schema.

Olivia Jensen

Olivia Jensen is a Business Advisor. She is passionate about trendy gadgets & bikes.


Join the conversation...