What is SQL ?
SQL is a powerful language designed for interacting with relational databases. Essential for both data analysis and supporting backend systems, it allows users to perform a range of tasks from basic data management to complex queries. With its wide adoption and ongoing evolution, SQL remains a fundamental skill in data-driven fields.
SQL (Structured Query Language) explained
SQL, short for Structured Query Language and pronounced as "S-Q-L," is a language designed for interacting with relational databases. SQL enables tasks like updating and retrieving data from databases.
An SQL database, also known as a relational database, is a structured collection of data organised into tables – which is addressable using a structured query language. It is the direct opposite of a NoSQL database. Each row in a table represents a data entity, and each column defines a specific information field. The data in these tables can be accessed, managed, modified, updated, controlled, and organised using SQL.
Common relational database management systems utilising SQL include Oracle, Sybase, Microsoft SQL Server, MySQL, PostgreSQL, MariaDB, and more.
While many database systems adopt a programming language like SQL, they often incorporate unique proprietary extensions specific to their platforms. Nonetheless, fundamental SQL commands like "SELECT," "INSERT," and "CREATE" are universally applicable for most database operations.
SQL is used to execute essential data management functions, but can also be used to build complex queries to transform available raw data into useful and contextual information. SQL experts can use SQL databases to get meaningful information by joining various tables to understand the data context and data relationships better. By programming a SQL language query, users can:
- Conduct targeted queries within a database or a set of relational data
- Fetch or modify existing records and data within a database
- Add new entries to a database
- Remove outdated records from the database
- Create new databases or establish new tables within an existing database to enhance organisation and optimization
- Develop stored procedures and views within a database
- Assign access rights for procedures, views, tables, and various data sets in a database
SQL databases have been around for decades and remain one of the most popular and widely used systems for storing and processing highly structured data. They are at the heart of many backend enterprise systems and are fundamental to the functioning of the electronic age.
A Short History of SQL
Structured Query Language was introduced in the 1970s by IBM researchers Donald D. Chamberlin and Raymond F. Boyce. They developed the programming language after learning about the relational model from Edgar F. Codd. The initial version of SQL statement was called SEQUEL (Structured English Query Language) and was designed to manipulate and retrieve data stored in IBM's original quasi-relational database management system, System R, which a group at IBM San Jose Research Laboratory had developed during the 1970s.
The first commercially available implementation of SQL programming was introduced by Relational Software, Inc. (now Oracle) in 1979. SQL was standardised by the American National Standards Institute (ANSI) in 1986, with standardisation by the International Organization for Standardization (ISO) following in 1987.
SQL servers offered two main advantages over older read-write APIs such as ISAM or VSAM. For a start, SQL introduced the concept of accessing many records with one single command. Secondly, it eliminated the need to specify how to reach a record, i.e., with or without an index.
Over the years, SQL server programming has undergone several revisions to keep pace with the evolving needs of the database industry. For instance, SQL:2011 added temporal data and enhancements for window functions and a FETCH clause.
SQL:2016 introduced row pattern matching, polymorphic table functions, and operations on JSON data stored in character string fields. SQL:2019 added Part 15, multidimensional arrays (MDarray type and operators) to SQL statements.
The evolution of SQL also included the development of various database systems. For example, Microsoft's MS SQL Server started in 1988 when Microsoft collaborated with Ashton-Tate and Sybase to develop database creation and maintenance software.
What is SQL used for?
Today, SQL is the most widely used language for managing relational databases and is an essential part of the technology stack for many organisations. It is used in business, government, and scientific applications across many roles including data analysts, business intelligence analysts, data scientists, database developers, and data engineers.
Marketing
In marketing, SQL programming is a valuable tool for data analysis. For instance, marketing executives like Anne use SQL to navigate through extensive customer databases. This involves extracting key information such as purchase history and customer demographics to refine marketing strategies and target campaigns more effectively.
Application development
For mobile and web development, using SQL statements is essential for data processing and ensuring secure data storage. It supports the integration of databases with applications, contributing to the functionality and security of these platforms.
Finance
The finance sector benefits from SQL in analysing sales data and forecasting. Finance professionals like John use SQL to identify trends and anomalies in sales, aiding in the development of informed financial strategies and planning.
Analytics
Data analytics heavily relies on SQL for extracting and analysing large datasets. This enables data analysts to uncover trends and insights that inform company strategies and decision-making. Business analysts use SQL statements for data collection and analysis, as well as for creating dashboards for management. The integration of SQL with tools like Tableau and PowerBI is crucial for presenting complex data in an accessible format.
Medical services
Healthcare also sees the application of SQL programming, particularly in managing patient data. Organisations use SQL to track disease patterns and allocate resources efficiently. This aids in patient care management and healthcare analytics, improving patient outcomes and service efficiency.
Data science
In data science, the SQL language is key for tasks like data extraction, preprocessing, and exploratory data analysis. It supports real-time applications such as dynamic pricing and fraud detection by efficiently handling large volumes of data.
How SQL Works?
The SQL programming language allows you to apply create, read, update, and delete operations (CRUD operations) to data and database objects. Some key components and aspects of how SQL works:
- SQL is a declarative language - you specify what you want to get/do, not how to do it. The database figures out how to fulfil the request efficiently.
- Data is stored in tables consisting of rows and columns. SQL allows you to query data from one or more tables. It can join tables together for queries.
- You write queries (commands) to perform CRUD operations and other logic.
Common SQL commands include:
- SELECT - Retrieve data from SQL tables
- INSERT - Insert new rows into a SQL table
- UPDATE - Update existing data in a SQL table
- DELETE - Delete rows from a SQL table
- CREATE - Create new database objects like SQL tables
- ALTER - Modify existing SQL database objects
Queries mostly consist of clauses like SELECT, FROM, WHERE, GROUP BY, ORDER BY. They tell the database what data to fetch, from which tables, any filtering criteria, if/how to aggregate it, etc.
You execute SQL language queries and commands to an instance of a relational database management system (RDBMS) like MySQL, Postgres, SQL Server, etc which manages storing the data and translating SQL into the necessary data CRUD operations. Results are returned by the database.
So in summary, a SQL database provides a standard language and syntax for operating on relational data in a database via simple declarative queries that tell the database what you want to achieve with the data.
What are the benefits of SQL?
SQL cloud databases offer several intrinsic advantages, including faster query processing, data consistency, security, and scalability. They enable efficient retrieval and manipulation of large amounts of data, ensuring data consistency across multiple tables through transactions.
SQL databases also provide built-in security features to protect data from unauthorised access and maintain data integrity. Additionally, they can handle large volumes of data and scale up or down according to the application's requirements. Some of the benefits of SQL programming for businesses and organisations include:
Efficient query processing
SQL server databases can retrieve, alter, or store data at high speeds, making it efficient for handling large volumes of data
Ease of use
Using SQL does not require extensive coding knowledge, making it accessible to a wide range of users. Its commands are easy to understand, even for non-programmers
Interactive language
SQL server provides easy commands for various purposes, making it an interactive language for its users. It can provide answers to complex queries in seconds
Multiple data views
SQL databases can handle large volumes of data and can be scaled up or down as per the requirements of the application
Security
SQL databases have built-in security features that help protect data from unauthorized access, such as user authentication, encryption, and access control
Data integrity
SQL programming ensures consistency of data across multiple tables through the use of transactions, which ensure that changes made to one table are reflected in all related tables
Portability
The SQL language is hardware independent and can be used on servers, personal computers, laptops, and even some mobile phones
High accessibility
SQL programming is compatible with most databases like Microsoft Access, MySQL, and others. Most relational database management systems support SQL functions, allowing for the development of application extensions
No need for extensive coding
SQL does not require large complex lines of code for data extraction, making it easy to maintain database systems.
SQL Queries: General Structure
The general structure of a SQL query is designed to be somewhat intuitive, resembling a simple sentence in English, and it typically follows a select-from-where pattern.
At the heart of most SQL queries is the "SELECT" statement. This is where users specify what data they want to see. Imagine a database as a collection of tables, each filled with rows and columns of data, much like a spreadsheet.
When a SQL programmer uses "SELECT," they’re pointing to the column(s) they’re interested in. For example, in a database with a table of books, one might use "SELECT title, author" to retrieve a list of all the book titles and their authors.
The "FROM" clause follows the "SELECT" statement and identifies the database table from which to retrieve the data. Continuing with our book example, if the table containing the book data is named "Books," the query would now look like "SELECT title, author FROM Books."
That tells the database server that the user is looking at the "Books" table and is interested in the title and author columns.
Extracting targeted information is performed using the "WHERE" clause. This part of the query is used to filter the data, specifying which rows the user wants to retrieve based on certain criteria. Say they only want books authored by "J.K. Rowling." The user would add "WHERE author = 'J.K. Rowling'" to your query.
The full query would then be "SELECT title, author FROM Books WHERE author = 'J.K. Rowling'." Now, instead of retrieving all rows from the "Books" table, you'll only get those where the author matches your specified condition.
These three components - SELECT, FROM, and WHERE - form the core of a basic SQL server query, but there are many more capabilities to SQL. It’s possible to sort results with "ORDER BY," group data together with "GROUP BY," and even combine data from multiple tables in more complex ways.
As users get more comfortable with SQL, they learn about joins, subqueries, functions, and other advanced features that allow for even more powerful and sophisticated data manipulation.
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