What Is SQL?

SQL, or Structured Query Language, is a domain-specific language that’s been in use since the 1970s. It’s still widely used in analytics, data engineering and data science to help manage data stored in a relational database system and can be vital when working with structured data. SQL allows programmers to query, update and reorganize data as needed while also modifying database schema to control data accessibility. MySQL and PostgreSQL are two of the most popular open-source relational database management systems while some common enterprise-level systems that utilize SQL include Oracle, Sybase, Microsoft SQL Server, Access, Ingress and many other proprietary extensions.

How Does SQL Work?

At its core, a database is simply a system for organizing data stored on disk. Relational databases work by storing structured data within tables. These tables make up the database schema, and oftentimes, these tables will be linked together through one or more common fields. These relationships between common fields allow users to access data from separate tables simultaneously upon user query. This process is called joining tables.

The tables and data within databases are stored in separate files on disk for easy access and permanent storage compared to data stored in memory. Understanding the database’s file system is an important part of architecting data intensive applications, but is not a requirement for learning and using SQL. 

For relational databases that use SQL, an SQL engine and query optimizer are used in conjunction with the file system. Together, they interpret and execute the SQL commands. The query engine transforms the SQL into something the computer can understand while the query optimizer finds the optimal way to retrieve the data from the files.

SQL Syntax 

The foundations of SQL and query optimization stem from relational algebra, but SQL is easy to learn and apply without knowing the theory upon which it was built.

To carry out any action in SQL requires a statement, which in essence is a set of rules and guidelines to interact with a database. A statement begins with a keyword such as SELECT, INSERT, UPDATE, DELETE, CREATE and DROP, followed by a clause or expression and ends with a semicolon. For example, the following statement creates a table called users with separate columns for name and email. 

CREATE TABLE users (
    name VARCHAR(100),
    email VARCHAR(255) UNIQUE,
);

In the example above, VARCHAR refers to the datatype and character length the column can accept. Other datatypes include INTEGER, BOOLEAN, TEXT and TIME,  and must be specified when creating a table.

SQL Joins

SQL Joins are one of the most used tools for data analysis using SQL. The JOIN clause is used to combine rows from various tables based on a related column like a unique ID. There are four different types of joins with each culling and organizing data differently. 

To join columns from multiple tables you need to select the columns and their table names location followed by a JOIN clause that defines how the tables are related. The statement for this action looks like the following:

SELECT 
  table1.columnA,
  table2.columnB,
FROM
  Table2 ON table1.common_column = table2.common_column;

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What Is SQL Used For?

Generally, we use SQL to communicate with a database. Every company stores data to some extent, which means having the skills to access and manipulate data can result in a high-paying career.

SQL is useful when it comes to managing structured data in an organized manner, thereby making it easy to quickly access and arrange data.

SQL is particularly useful due to its ability to share and manage data found in a relational database management system, which allows users to query, update and reorganize key data, while also modifying database schema and determining how data can be accessed.

Due to these capabilities and use cases, SQL has become the most widely implemented programming language despite being created in the early 1970s.

SQL In Data Science

SQL is one of the fundamental tools used in data science, alongside Python and R. Data scientists use it to find, manipulate and extract information from a database. SQL is also often the first step in the analytics process and can be used to gather data for reports, visualizations and machine learning models. Additionally, it can be used to find user trends in product development. 

SQL In Finance

SQL has multiple uses in the financial industry. For example, it can be used to monitor transactions, generate financial reports, analyze risk and detect suspicious behavior. SQL can also be used to build forecasting models for revenue and cash flow. 

SQL In Healthcare

In the healthcare industry, SQL can be used to analyze patients records and health data while maintaining HIPAA compliance. Analysts use it to identify patterns and treatment outcomes across populations as well. SQL is also used on the insurance side to analyze medical insurance claims. 

Should I Learn SQL or Python?

Oftentimes, working with structured data requires fetching the data in SQL and manipulating it in Python, so the short answer: Learn both if you can.

SQL is excellent for querying, extraction and merging tables from databases together to provide users with robust but specific datasets. SQL is not, however, the best choice when it comes to transforming data into other formats, which is often utilized in the form of regression testing and time-series data manipulation in data science. Python is the better option for tasks of this nature, particularly through its Pandas library, which is tailor-made for data manipulation and analysis.

Frequently Asked Questions