We are living in the Big Data era. Every time we go online, we provide the websites we visit with a lot of information. If we voluntarily give our data by creating an account, filling out a form, or making a purchase, we give them even more information. All this data is recompiled and centralized in companies’ huge databases. And then what happens to it?

Every department in the company needs this data! If the e-commerce manager wants to monitor the website’s daily conversion, she needs the data. If the company’s country manager needs to create a detailed report of the quarter’s activity, he needs the data. If the marketing team wants to build a remarketing campaign to reengage old clients, they need the data. If the executive board wants to establish strategies for the next years, their decisions will be based on data.

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You may be wondering why we write about Python on the LearnSQL.com blog? Well … They are just a very good couple. Both languages are basic tools in such fields as data science and data visualization. They complement each other perfectly and strengthen their individual capabilities.

That’s why I decided to show you how much you can gain by learning the basics of Python. I know that many people reading this article are still on the path of learning SQL and do not currently have the space to learn another skill. It’s usually best to master one skill – in this case, SQL – and then move on to the next challenge.

However, it is worth planning your development path in advance. That’s why I decided to describe how using SQL with Python will help you spread your wings and boost your career.

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If you’re interested in learning more about SQL but have no prior knowledge of programming or databases, take a look at our SQL Basics course.

SQL is a standard, meaning it is a reference. Read about the history of the SQL standard in our article “The History of SQL Standards.”

In practice, each database system uses its own version of SQL, usually called an SQL dialect. SQL dialects are like dialects in the linguistics sense; they are mutually comprehensible. You don’t need to know every SQL dialect; their differences are very slight.

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SQL concatenation is the process of combining two or more character strings, columns, or expressions into a single string. For example, the concatenation of ‘Kate’, ‘ ’, and ‘Smith’ gives us ‘Kate Smith’.

SQL concatenation can be used in a variety of situations where it is necessary to combine multiple strings into a single string. Some common use cases include:

• Creating full names or other composite strings from multiple columns in a table – e.g. concatenating a user’s first and last names to create a full name.
• Creating custom labels or titles by concatenating multiple string values.
• Creating a unique identifier by concatenating multiple columns – e.g. a customer ID and an order number.
• Creating email addresses by concatenating a username (katesmith) and a domain name (learnSQL.com).

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So you want to land yourself a database job in 2023. It’s a great choice, and there are lots of options. Let’s talk about the most popular data-related jobs and what you need to do to get one.

SQL Is Essential for a Database Job

It’s important to mention that most of the popular databases nowadays are relational – i.e., PostgreSQL, MySQL, Oracle, and MS SQL Server, among others. You can find more details in the article The Most Popular Databases in 2023.

SQL is the language we use to communicate with relational databases. Knowledge of SQL is imperative if you want to work with databases. All SQL database systems use the standard SQL query language with small variations, usually called SQL dialects. Don’t be afraid; all SQL dialects are, like our spoken dialects, generally mutually comprehensible.

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If you already know the basics of SQL, you probably have figured out that most online and offline SQL tutorials and courses usually cover the basic and intermediate concepts: SELECT, FROM, WHERE, ORDER BY, GROUP BY, and joining tables. Even university database courses typically don’t cover more advanced  SQL topics.

While this is enough SQL for most everyday tasks, there are some relatively new features that have been added to SQL in the last 20 years: window functions, recursive queries, and GROUP BY extensions (ROLLUP, CUBE, GROUPING SET). So, what do you do if you want to learn to use SQL’s advanced features?

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If you are a software developer, you may have noticed that SQL skills are often required in some development roles. Although you are not a database manager or a data scientist, you will need solid SQL foundations to continue your developer journey.

Online courses are an obvious choice for learning SQL. I sincerely recommend our SQL Basics course for beginners or our SQL from A to Z track for people who want to learn everything SQL has to offer. Our courses combine knowledge with hands-on practice; you can write SQL queries in the interactive console and get instant feedback. All you need is the Internet and your favorite browser.

Why Is SQL Necessary for Software Developers?

SQL is a programming language used to communicate with relational databases and other data technologies. Even if you don’t use relational databases, your data technology of choice likely understands SQL as a query language. Moreover, relational databases are a very mature and stable technology and are used in many software projects. Your main technology may be different, but there is probably a relational database somewhere in your project; it’s good to know the basics of how to work with them. Let’s see some practical cases where you will have to know SQL.

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PostgreSQL has gained popularity in the last decade, and many developers and database specialists learned PostgreSQL as their first SQL dialect. But PostgreSQL is not the only relational database; during your IT career, you will probably be asked to use another SQL dialect – like MySQL.

You may wonder whether you would struggle with MySQL after learning PostgreSQL. In this article, we’ll discuss how difficult it is to switch from PostgreSQL to MySQL.

If you are brand new to MySQL and you want to know all the fundamentals, I strongly recommend you try our complete SQL from A to Z in MySQL track. It will give you the full working proficiency you need to boost your career.

A Byte of History

Computer scientist Michael Stonebraker started developing Postgres (an evolution of an earlier database system and the forerunner of PostgreSQL) in the 1980s; in 1996, Postgres became PostgreSQL. You can read more on the history of PostgreSQL elsewhere in our blog.

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Many of us developers and database specialists began working with free relational databases like PostgreSQL or MySQL for personal projects or small organizations. Some of us have since moved on to organizations using MS SQL Server and have had to learn to use the new tool.

You may be wondering how challenging that is and whether you would struggle with SQL Server under similar circumstances. In this article, we discuss whether it is difficult to switch from PostgreSQL to MS SQL Server.

If you want to become an SQL master, the track SQL from A to Z on LearnSQL.com is highly recommended. It gives you everything you need to know to work with databases and analyze data efficiently.

A Byte of History

Michael Stonebraker is an American computer scientist specializing in database systems. He first developed Ingres, a proprietary SQL relational database management system, at the University of California, Berkeley.

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