SQL, or Structured Query Language, is the most commonly used language for retrieving and organizing data from relational and multidimensional databases. SQL has been around for over four decades and is an industry-standard in various business fields, especially those that handle data like data analytics. SQL allows Data Analysts to access, organize, and analyze large stores of data so that patterns can be spotted and insights can be provided that will help inform a company or organization’s decision-making process.

SQL is used as a data definition language (DDL), and can autonomously create a database, and once it is not being used, dispose of it. Additionally, it is a data control language, (DCL) since it can be used to maintain an already existing database. Because it is also a declarative language, SQL is considered to be a programming paradigm, which allows it to build the structure and various elements of a computer program that reflect the logic behind the computation without expressing its control flow. In addition, SQL is often used as a server language because users can interface the front end with the back end.

For those who are interested in working with the open-source version of SQL Server, MySQL is available. MySQL is a relational database management system, just like SQL. Whereas SQL Server is a licensed Microsoft product users have to pay to use, MySQL is free and open-source. MySQL also differs from SQL Server in terms of the languages it supports, as well as storage space, query cancellation capabilities, and capacity for data file manipulation.

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Main Uses for SQL

In 2020, 1.7 MB of data were created every second, a number that’s likely to expand as our reliance on technology continues to increase. In data-driven roles in particular, it’s crucial to stay informed of various technical tools and programming languages to keep up with the ever-evolving field of big data. Those who know how to use SQL have a distinct advantage when applying for data jobs. All of the major DBMS (database management systems) integrate with SQL, which means that those who have an understanding of this language have a competitive edge over the competition.

SQL has a wide range of applications for both data analytics as well as data science. It is most commonly used to:

  • Retrieve data from a database
  • Insert, update, or delete records from a database
  • Design new databases and tables
  • Perform queries against a database
  • Establish permissions on procedures, views, and tables
  • Create views, functions, and storing procedures

Many of the biggest players in the tech industry use SQL. Companies such as Netflix, Uber, Airbnb all use SQL when working with data. In addition, companies like Google and Amazon, which use database systems of their own construction, still rely on SQL for their data querying and analysis needs.

Why Data Analysts Should Know SQL

SQL’s most popular use today is as a base infrastructure that allows users to create dashboards and reporting tools. Complex instructions can be effortlessly communicated to databases, and data can be manipulated in just seconds. Its ease of use allows users to display data using intuitive dashboards, which are capable of illustrating data in many ways.

When SQL is used for data analysis, the database’s querying language simultaneously interacts with multiple databases and also uses relational databases. This flexible language is accessible to users while at the same time providing the necessary depth to allow for the creation of advanced dashboards and data analytics tools. Although SQL’s language is simple, it’s able to perform complex data analysis.

While SQL remains commonly used by Software Developers and Engineers, it’s also very popular among Data Analysts for several reasons:

  • Vast amounts of data can be accessed directly where it is stored so that Data Analysts don’t have to copy data into other apps.
  • It is easy to understand and use.
  • Unlike spreadsheet tools, analyzing data in SQL is easy to replicate and audit.
  • SQL has a variety of proprietary tools with their own specific focus, such as Microsoft SQL Server, PostgreSQL, and MySQL, that allow users to quickly create and interact with databases.
  • It’s a powerful tool for creating data warehouses due to its accessibility, interactivity, and straightforward organization.

According to a 2020 survey of over 10,000 data professionals, 65% of Data Analysts reported using SQL, compared to 64% who used Python and 28% who used R. This means that SQL remains the most popular language for those working with data, and continues to be one of the core programming languages for developers in all disciplines.

Hands-On Data Analytics & Coding Classes

Are you interested in learning more about data analytics? If so, Noble Desktop’s data analytics classes are a great starting point. These small classes are taught by top Data Analysts in New York. They are open to students from all educational backgrounds and require no prior coding experience. Noble offers live online data analytics courses in topics like Python, data analytics, and Excel, among others skills necessary for analyzing data.

For those looking to break into computer programming, learning SQL is a great place to start. Because it has a simple language structure and is a free, open-source application, studying SQL enables users to gain experience with manipulating and interpreting data, which can help prepare them to eventually work with more complicated coding languages.

Students who are interested in learning how to code can enroll in one of Noble Desktop’s coding bootcamps. Courses are available in front end web development, back end web development, full stack web development, FinTech, and software engineering, among others. Those looking to work specifically with SQL can enroll in Noble’s SQL Bootcamp. This 18-hour course covers fundamental concepts like basic queries, as well as advanced concepts like aggregating and joining.

Noble’s Coding Classes Near Me tool provides an easy way to locate and browse more than 500 coding classes currently offered by top providers near you in in-person and live online formats. Course lengths vary from two hours to 72 weeks and cost between $149 to $27,500.