What Does SQL Stand For?

Written by Coursera • Updated on

Discover an overview of the acronym SQL, the job prospects for someone with SQL skills, and salary expectations and educational requirements for a computer scientist or data science engineer career.

[Featured image] A smiling data analyst in a blue shirt sits in front of a computer monitor that displays computer code .

The SQL acronym stands for Structured Query Language. It is a universal programming language used to manage relational databases (RDBMS). Many relational database systems support the SQL language, including MySQL, SQL Server, and Oracle. 

What is SQL?

SQL is a universal programming language that acts as a database manager. SQL provides many advantages for businesses and organizations that rely on a database management system. No coding skills are needed, and it’s interactive so all users can understand the data. It was named the standard language in 1986 by the American National Standards Institute ANSI). 

SQL is beneficial to companies and organizations that handle large quantities of data and need to streamline it or make changes. With SQL, the user can insert, delete, and update records. Its setup is formatted like an Excel spreadsheet with columns and rows.

How can SQL be used?

SQL can be used to find information quickly and efficiently. You can use SQL to locate the data sets you need, and “create” a new database and add tables. SQL allows you to update information easily and delete any individual records or tables you don’t need.

A user does not need coding skills to work with SQL. The commands are all that are needed to use and understand the data. The primary language is English, and SQL can be used on PCs and laptops. SQL is also adaptable on some mobile devices for portability.

History of SQL

The SQL language traces its origins to the 1970s when IBM developed a new database program called System R. IBM created the SQL language to manage the data stored in System R. It was first called SEQUEL (an alternative pronunciation of SQL) but later changed to SQL.

The company Relational Software, which would become Oracle, saw the commercial potential of SQL in 1979 and modified it for its use, naming it Oracle V2. The SQL language has existed for more than three decades now. It offers excellent flexibility through support for distributed databases—databases that can simultaneously run on several computers. 

With the certification of ANSI and ISO, SQL is recognized as a database query language standard, which forms the basis of numerous Internet databases. In addition to being used on individual computers and corporate servers, it also serves industry-level and academic needs. SQL-based applications have become increasingly affordable for regular users due to advancements in database technology. Consequently, open-source SQL databases such as MySQL, PostgreSQL, and SQLite have become more popular.

What is a database?

Databases are searchable collections of data structured and stored electronically in the cloud or on a computer system. A complete database system encompasses the data, a database management system (DBMS), and associated applications unique to the database.

Most databases consist of a series of tables made of rows and columns, which serve to facilitate faster querying. A database allows easy access, management, modification, updating, and control of data. 

 Database types vary, and the data you wish to store will determine which type you use. Here's a look at some popular types:

Relational databases

A relational database contains organized units, usually in the form of tables, relationally arranged within a database. Relational databases can break down data into logical, smaller, and more manageable units for better performance and easier maintenance.

NoSQL databases

Unlike relational databases, "NoSQL" databases store information in document format instead of relational tables. These databases work best for enterprises that may not know their data requirements upfront or for businesses and other entities that deal with a large volume of unstructured data. They are scalable, allowing the flexibility to meet growing data demands. 

NoSQL databases are more intuitive due to their flexibility, and databases can be categorized according to their data models. The main types include documents, key values, wide columns, and graphs.

Read more: NoSQL vs. SQL Databases: Understand the Differences and When to Use

Cloud databases

A cloud database is any database that runs as a service within the cloud. It offers flexibility and is low maintenance. One example is the Oracle Autonomous Database.

Time series databases

Time series databases feature time-stamped data, offering more accurate insights. One such database is Druid.

Benefits of SQL

SQL is widely used for database access because it can access any database. Benefits of using SQL include the following:

  • SQL provides users with access to data in relational databases.

  • It is easy to identify and modify data in a database using SQL.

  • The database can be modified by adding, deleting, and altering data.

  • Other languages can embed SQL modules, libraries, and pre-compilers.

  • SQL allows you to build database views, stored procedures, and functions. 

Types of SQL commands

Using SQL commands, you can interact with the database to perform specific tasks, such as functions that allow you to query the database. SQL commands are instructions coded into SQL, and most database actions are performed using SQL commands.  Depending on their functionality, SQL commands may be categorized as follows:

  • Data Manipulation Language (DML)

  • Data Definition Language (DDL)

  • Data Query Language (DQL)

  • Data Control Language (DCL)

  • Transactional and Control statements

  • System control statements 

SQL vs. NoSQL: comparison & differences

Database experts choose or suggest a database, and the "SQL vs. NoSQL" comparison is a helpful guide for making informed choices. One must consider both databases based on vital data requirements and acceptable tradeoffs conducive to achieving performance and availability targets.

To decide whether to use an SQL or NoSQL database, you will want to understand some of these critical differences.

FeatureSQLNoSQL
ScalingBecause of their vertical scalability, you can add more RAM or CPU to your single server to increase storage space in most SQL databases.Databases built with NoSQL technologies are horizontally scalable, meaning that you can expand them by adding more servers. NoSQL databases are more distributed because you can expand them with additional servers.
Data Structure/ModelsStructured data works better with SQL or relational models. Data structured in this way is easy to locate, search, and analyze, similar to data organized in a table.Because NoSQL models don't rely on a predefined model, they are a good fit for less structured data sets.
Popularity and ease of useSQL databases allow for easy access to complex data.Unstructured data is best suited to NoSQL databases.

Career paths in SQL

Databases are essential to the day-to-day operations of many businesses today and are used across virtually all industries. Many large enterprises that most people recognize depend on SQL. These include Google, Amazon, Wells Fargo, and Netflix. However, careers for those fluent in the use of SQL are not limited to companies with a large online presence. SQL is used across a wide array of industries, from streaming services to refineries. Knowledge of SQL will expand career opportunities across all IT-related fields, engineering, and data science.  

Some titles, salaries, and job outlooks related to SQL are: 

  • Database administrator

    •  Median annual salary (BLS.gov): $101,000 [1]

    • Job outlook (projected growth from 2021 to 2031):9% 

  • Software engineer/developer

    • Median annual salary (BLS.gov): $109,020 [2]

    • Job outlook (projected growth from 2021 to 2031)25%

  • Journalists

    • Median annual salary (BLS.gov): $48,370 [3]

    • Job outlook (projected growth from 2021 to 2031): -9%

  • Computer systems analysts

    • Median annual salary (BLS.gov): $99,270 [4]

    • Job outlook (projected growth from 2021 to 2031): 9%

Steps to learning SQL

SQL does not require extensive programming knowledge. If you’re interested in getting to know SQL, try a course on learning SQL basics. It is still worthwhile to learn SQL, even if you're not a data scientist or backend developer. Taking charge of your company's data will allow you to discover valuable insights without waiting for your technical colleagues. 

You can learn advanced SQL techniques for marketers and product managers once you've mastered the basics of SQL programming.

Ready to start a career in SQL and data management?

Skills in programming, analytics, technical, and problem-solving are essential for careers in database management. Getting a degree allows you to refine your abilities and learn how to use them professionally.

Depending on your career goals, you may need a particular level of education. Many database management careers require a bachelor's degree, while others require a master's degree. However, some only require an associate degree or technical certification. You can often advance your career and earn more money depending on your education level.

If you’re interested in learning SQL, consider completing the Google Data Analytics Professional Certificate online on Coursera. You'll gain skills like Tableau, R, spreadsheets, data visualization, and SQL expertise.

UC Davis University of California offers a course covering SQL for Data Science for beginners, and it offers a course in Data Science Specialization. Both certificate programs can be completed online.

Certificate courses can teach you about SQL, improve your skills, and enhance your resume. Courses can be completed online and some courses, such as Google Cloud SQL for SQL Server can be completed in one hour. 

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Article sources

1

US Bureau of Labor Statistics. "Database Administrators, https://www.bls.gov/ooh/computer-and-information-technology/database-administrators.htm#tab-1." Accessed October 26, 2022.

Written by Coursera • Updated on

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