What is SQL?
SQL (pronounced "ess-que-el") stands for Structured Query Language. SQL is used to communicate with a database. According to ANSI (American National Standards Institute), it is the standard language for relational database management systems.
SQL statements are used to perform tasks such as update data on a database, or retrieve data from a database. Some common relational database management systems that use SQL are: Oracle, Sybase, Microsoft SQL Server, Access, Ingres, etc. Although most database systems use SQL, most of them also have their own additional proprietary extensions that are usually only used on their system.
SQL was developed by IBM in the 1970s for use in System R, and is a de facto standard, as well as an ISO and ANSI standard. SQL offers two main advantages over older read/write APIs: first, it introduced the concept of accessing many records with one single command; and second, it eliminates the need to specify how to reach a record using low-level address pointers.
Structured Query Language Meaning
Because SQL is the agreed upon language for queries in a relational database management system, it is essential for everyone working in data to have a thorough understanding of it. Queries are the ability to ask the data questions, and the method of searching and discovering data. Being able to interact with data using SQL is essential to the role of being a data steward.
SQL statements are used to perform tasks such as update data on a database, or retrieve data from a database. Some common relational database management systems that use SQL are: Oracle, Sybase, Microsoft SQL Server, Access, Ingres, etc.
Although most database systems use SQL, most of them also have their own additional proprietary extensions that are usually only used on their system.
However, the standard SQL commands such as "Select", "Insert", "Update", "Delete", "Create", and "Drop" can be used to accomplish almost everything that one needs to do with a database. This tutorial will provide you with the instruction on the basics of each of these commands as well as allow you to put them to practice using the SQL Interpreter.
Uses & Applications
SQL in a database can be used for:
- Creating a new database and inserting data into it
- Deleting data within the database
- Changing or moving data from one table or dataset to another
- Changing and setting permissions for the data (i.e. who can view what, who can change what within a database).
How SQL queries work
A SQL query works by allowing users to communicate with a database to retrieve, manipulate, or manage data. When you write an SQL query, you're essentially giving instructions to the database management system (DBMS) on what data you want and how you want it processed. The query is composed of specific SQL commands like `SELECT`, `INSERT`, `UPDATE`, or `DELETE`, which tell the DBMS what action to perform.
When the query is executed, the DBMS processes it in several steps. First, it parses the query to check for syntax errors. Then, it creates an execution plan, determining the most efficient way to retrieve the requested data. The DBMS may involve scanning tables, applying filters, and joining multiple tables if needed. Once the execution plan is in place, the database fetches the data and returns the result set to the user. This process happens behind the scenes, enabling users to interact with complex databases using simple, structured commands.
Using SQL begins with a command, which is carried through a SQL engine and then interpreted. As per tutorialspoint.com, the components in this process are as follows:
- Query dispatcher
- Optimization engines
- Classic query engine
- SQL query engine
Why use SQL instead of Excel?
SQL is preferred over Excel for managing large datasets, performing complex queries, and ensuring data integrity. While Excel is suitable for smaller data tasks and simple calculations, SQL excels in handling vast amounts of data, enabling efficient querying, and managing relational databases. SQL also offers more robust data security and automation capabilities, making it ideal for enterprise-level data management and analysis.
.svg)
