SQL joins and DashboardFox go hand-in-hand, that goes without saying.
Our company motto is “Bring Your Data to Life.” And while our software is designed to make that easy and secure, during the setup and configuration process there are a few technical things you need to do. One of the more important tasks is to build the semantic layer, we refer to as a DashboardFox App.
In the process of building that semantic layer, SQL joins are an invaluable tool.
How much do you know about these clauses, the different types, and when to use them?
Much of the information that’s currently available on SQL joins is highly technical, full of confusing code examples, and difficult to understand. Luckily, we’re here to fix that.
This guide will help you understand the basics of SQL joins, including why they matter and when to use the different types. You can then take this information and use it to improve your data management strategy.
What Is an SQL Join?
An SQL join allows you to logically combine records from two or more unique SQL tables. You can also use joins to retrieve data based on common fields shared among multiple tables.
When an SQL query features a join, the relational database management system (RDBMS) will search for data in all the tables you include within that join. It then combines the results and presents them in a new table.
In general, you will use SQL joins when you need to retrieve data from tables that share either many-to-many relationships (multiple records are shared across the tables) or one-to-many relationships (one record in one table is associated with many records in another table).
Why Are SQL Joins Important?
Regardless of your industry or company size, SQL joins are a critical part of an effective and efficient data management strategy.
The following are some of the top reasons why you need to understand and properly utilize them:
SQL Joins Are More Efficient
At some point in your career, you’ll likely find yourself in a situation where you need to combine data from two or more tables. SQL joins to provide you with the most efficient way to do that.
Imagine you had a table that included the names of all the students in a grade and all of their classes. If you wanted to change one student’s name, you’d have to change it multiple times to ensure it’s consistent across all their different classes.
To accomplish this, you could separate all the data into a student table and a classes table.
This option would make it easier for you to update the student’s name. However, it wouldn’t make your job easier overall and would take a lot more time in the long run.
After you separated the tables to make the name change, you’d then have to put everything back together in a table that would help the database answer other important questions. With SQL joins, though, you have a faster option.
SQL joins will help you complete this task faster, producing the same results in less time.
SQL Joins Maintain Normalized Databases
Normalization is a process of organizing data in databases. It includes table creation and establishing relationships between those tables based on certain rules.
Normalization helps you to reduce data redundancy, allowing for fewer data anomalies when you delete or update records.
Reducing redundancy also prevents wasted disk space and saves you from many potential maintenance problems (which will also slow down your process and interfere with productivity).
SQL joins maintain normalized databases and save you from having to do extra work to fix redundancies, wasted space, etc.
SQL Joins Reduce Database Workload
SQL Joins also reduce the workload placed on the database because you can use one join query to get the same result as multiple queries. Why would you wear yourself (and the database) out with multiple steps when one step produces the same thing?
When you reduce the database workload, you can make better use of the database’s various functions (search, filter, sort, etc.).
You can also work more efficiently and reduce your chances of experiencing time-consuming (and potentially costly) maintenance issues, freeing yourself up to focus on other important aspects of your job.
SQL Join Types
The essential components of an SQL join include:
- At least two tables
- A specific join condition
The tables feature rows that you’ll combine, and the join condition provides instructions for which rows will be matched together.
There are several different types of SQL joins you can use to combine data from tables (the type you choose will depend on your goals). However, the following are some of the most commonly used joins you should be aware of:
An inner join is the most popular type of SQL join, and it’s also the default option in most situations.
Inner joins offer results only when matches exist between both tables included in the join query (you can use SQL joins to combine more than two tables, but to keep things simple, we’ll only use examples with two tables in this guide).
For example, say the two tables included the same employee name, product ID, or department name. Those matching records would show up in the resulting table.
If records in the two tables do not have a relationship, they won’t appear in the query results. Because of this, you’ll only use an inner join when you require related data inputs from both tables and don’t mind if certain records are eliminated from the new table.
A left join (also known as a left outer join) is similar to an inner join in that it combines rows from two tables. There is a critical difference, though.
A left join also includes all the data from the left table (hence the name), even if there’s no corresponding relationship between that data and the right table.
In situations where you want to focus primarily on the data in the left table, a left join is useful, as it saves you from accidentally deleting vital data inputs that you’ll need to reference later.
A right join (or right outer join) is the exact opposite of a left join. It combines rows from two tables and includes all the results from the right table.
Right joins aren’t as common as left joins because many developers place the primary table on the left (perhaps because they read left to right). However, right joins still come in handy in scenarios where you want to focus on the right table data and don’t want to accidentally omit it.
Full Outer Join
A full outer join will return all of the rows from both tables in the resulting table.
If there’s a relationship between the rows, they’ll be combined in the join result. However, if a relationship doesn’t exist, the result will include NULL values to fill in the gaps.
If you want to include all the data from both tables, even when there aren’t relationships between certain rows, a full outer join is the easiest option to get that result.
A cross-join is also known as a Cartesian join. It combines all of the left table’s rows with all the right table’s rows. The result is a breakdown of every possible combination of rows.
For example, say you had a table of car models and another table of car colors and wanted to know all the different ways they could be combined. In that case, a cross join would be the most efficient option to provide you with all the possible model-color options.
How to Decide Which SQL Join to Use
Sometimes, it’s obvious when you need to use an inner join, left join, etc. In other situations, though, you might be confused about the best way to proceed.
When that confusion arises, these guidelines can help:
- Use an inner join when: You don’t need to show all the records from the first table or all the records from the second table.
- Use a left join when: You need to show all the records from the first table, but you don’t need to show all the records from the second table.
- Use a right join when: You don’t need to show all the records from the first table, but you do need to show all the records from the second table.
- Use a full join when: You need to show all the records from the first and second tables, and you need to join the tables based on one or more columns.
- Use a cross join when: You need to show all the records from the first and second tables, but you don’t need to join the tables based on one or more columns.
For more clarity, you can also use this table as a reference point:
Don’t worry if these guidelines don’t make sense right away. With some practice, it’ll soon become second nature to use SQL joins and decide which type is most appropriate for your specific situation and the type of data you’re trying to manage.
How Can DashboardFox Help?
In conclusion, DashboardFox offers a powerful solution for businesses seeking to streamline their reporting processes and empower non-technical users.
With the App Builder role, constructing a semantic layer and organizing fields for intuitive use has never been easier. Plus, are you still not sure if you want to try to do it yourself? Just reach out and get the assistance of the DashboardFox team; it’s what separates us from other BI tools: we support the customer, not just the software.
Plus, DashboardFox’s one-time payment scheme allows for more long-term financial flexibility without worrying about maintaining subscriptions.
Don't let complex reporting processes hold your business back – try DashboardFox today and experience the benefits of simplified reporting.