You may think that programming languages created decades ago might become obsolete and only a few people must be using them. Structured Query Language or SQL is one such language introduced around half a century ago and you may have a first impression that it must be dead. However, it is still among the top programming languages most commonly used by professional developers. Surveys by Stack Overflow and TIOBE Index are proof of SQL’s growing popularity.
Basically created with an aim to help programmers excel at relational database management systems, SQL has come a long way and is now used in data science as well. Though people would suggest you prioritize learning Python, Java, Scala, and other advanced programming languages, ignoring SQL will make it harder for you to get a data-related job.
SQL is used by many popular technology companies like Airbnb, Facebook, Google, Amazon, Microsoft, Dell, Accenture, and many more. For most of today’s trending jobs like data scientist, data analyst, machine learning engineer, or full-stack web developer, companies list SQL as a must-have skill. Knowledge of SQL basics will position you ahead of your peers and more likely to grab the attention of hiring managers.
Let us know more about SQL and what are the basic concepts covered in this language.
SQL is a simple but powerful language that is used to perform a variety of operations on relational databases. It is the de facto language when it comes to data manipulation in a database management system. This is how the language comes into the picture when we talk of data science. The field involves cleaning, processing, and analyzing data by extracting it from the database. As many database platforms are modeled after SQL, people need to learn it when starting a career in data science. In fact, modern big data systems like Spark, Hadoop make use of SQL to maintain relational database systems and process structured data.
A relational database is known to store data which contains the pre-defined relationship between them in the form of tables having rows and columns. Through SQL commands, you can manipulate that data and use it as required. The SQL commands basically fall under the following five heads:
- Data Definition Language (DDL) – Create, Drop, Alter, Truncate
- Data Manipulation Language (DML) – Insert, Update, Delete
- Data Control Language (DCL) – Grant, Revoke
- Data Query Language (DQL) – Select
- Transactional Control Language (TCL) – Commit, Rollback, Savepoint
As you can infer, these commands are instructions used to communicate with the relational database. You can perform specific tasks, use functions, and queries of data, and then save it for further use. Similarly, using control commands, you can grant/revoke user access privileges to a database.
After knowing the SQL commands, we would recommend you to write some SQL queries and perform basic operations on the table. Practicing what you learn in theory is the best way to learn any language and use it from an industrial point of view.
Next, you should know about the joins in SQL. As the name suggests, SQL Joins are used to combine two or more table records in a database. Using Joins allows users to summarize data that would usually be stored in different tables into one resultant set. Here are the different types of Joins covered in SQL:
- INNER Join – It selects only the records with matching values in both the tables to be joined.
- FULL Join – It returns all the records when there is a match in either left or the right table.
- LEFT Join – It selects records from the left-most table along with the matching records from the right table.
- RIGHT Join – Contrary to the Left join, the Right join returns records from the right-most table along with the matching records from the left table.
Now, if you are learning SQL for its use in data science, then here are the important topics to master – GROUP BY clause, aggregation functions, string functions and operations, output control statements, and data and time operations. Additionally, you should become familiar with concepts like nested queries, arithmetic operators, logical operators, views, indexing, temporary tables, windowing functions, and query optimizations.
Learn SQL Today
Given the high demand for SQL skills for various job roles, you should start learning SQL if you haven’t decided already. There are thousands of tutorials and online courses available over the internet to help you learn SQL fundamentals. However, most of them don’t prepare you for using SQL in the real world. So, it is important to learn SQL from a reputed training provider. Simplilearn, Coursera, edX, Codecademy, and Udacity are some of the reliable edtech platforms offering high-quality course material on SQL and making you job-ready.
SQL has established itself as the standard data access language across different industries. This means it is not only used by developers, but professionals from different parallel technical fields as well that need to store, manipulate, and access large volumes of data. This is the reason SQL isn’t going anywhere. You can’t go wrong learning SQL now if you are embarking on a career in the technical field or anything that involves managing data.