Is SQL Worth Learning? 8 Reasons Why It Indeed Is

Structured Query Language, better known as SQL, is a non-procedural language that first became commercially available in 1979. The question is, for such a legacy language, is it still worth learning?

SQL is worth learning as an interfacing language for relational databases. For everything from running data queries, data mining, client-server access, data manipulation, and more, SQL knowledge is beneficial to data analysts across multiple fields.

If you are currently on the fence as to the value derived from learning SQL, this article will present you with a series of reasons why learning SQL is worth your while.

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Basic Functionality of SQL

To better appreciate why learning SQL is valuable, you should first understand what basic functionality the language performs.

SQL allows those working with data to interact with a relational database management system using a non-procedural language. In other words, it will enable you to tell the system what data you need for a specific query without having to specify the operations required to process it. In this sense, it functions more like an interface than a programming language.

It also simplifies the process of running complex queries on large or multiple databases and tables. Such facilitation makes SQL ideal for data analysts and other data managers who need to run complex queries for pattern detection and information pertinent to strategic and operational decision making.

If the purpose of SQL is primarily to query relational databases, why is it important to learn it? After all, some analysts only need to process queries prepared for them. It would seem that unless you are directly responsible for managing a database, learning SQL might be overkill.

The reality of the situation is that regardless of where on the data management chain you belong, learning SQL will provide you with operational efficiencies that will improve your overall job performance. Here are some of the most compelling reasons.

8 Reasons Why SQL Is Worth Learning

SQL Is Adopted As Standard By ANSI and ISO

SQL has had such staying power because it has been adopted as a standard by both the American National Standards Institute (ANSI) and the International Organization for Standardization (ISO).

SQL has achieved widespread use in being adopted as a standard, becoming the de facto language for interfacing with relational database management systems. As such, its continued presence for the years to come is practically ensured. Therefore, in learning SQL, you are not running the risk of acquiring knowledge in a language that will suddenly become obsolete.

SQL Is Used On Multiple Frameworks

Being an ANSI and ISO standard means that SQL is in use on multiple frameworks. There are many implementations of SQL from many vendors. MySQL, Oracle SQL, Microsoft SQL, and SQLite are some examples.

With SQL found in so many frameworks, your SQL skills are marketable to a larger crop of potential employers and clients. Each implementation of SQL has some variation in the use of syntax and commands. However, there is sufficient standardization that the learning curve is not very steep, even when moving to a different variation.

In other words, by learning SQL, even if it is vendor- or implementation-specific, you are not locked in that instance. Migrating your SQL skills horizontally to other frameworks is made easier through standardization.

SQL Knowledge Is Still a Highly Coveted Skill

The widespread use of SQL also makes it a highly coveted skill by employers and clients.

This demand translates into more advantageous terms for those who have learned SQL. According to the salary comparison company, Payscale, a senior statistician with SQL skills, has a median annual income of 1.3 percent higher than one without SQL skills.

This same comparative study also demonstrates that data analysts and data scientists with SQL skills also have median annual incomes of 4.8 and 1.6 percent higher, respectively.

Business and marketing analysts with SQL knowledge compared to those without SQL skills have the highest demonstrable bump in median annual income. Business analysts earn 7.5 percent more while marketing analysts 9.5 percent more.

From a skill marketability and compensation perspective, learning SQL has clear benefits.

SQL Can Handle Data Mining

If you conduct predictive analysis, data mining is crucial to your workflow. The deeper and faster you can access as large an amount of data as possible, the more effective your analysis will be.

SQL can make data mining very useful. However, you need to have the skills to write and fine-tune your SQL queries to get the most out of this type of data analysis.

Once you do, you will be able to use data mining to locate patterns, find aberrations, and be better able to create accurate forecasts. Data mining is essential if you assist in the preparation of strategic enterprise-level initiatives or streamlining operational procedures.

SQL knowledge frees you from the limitations of relying only on a handful of queries prepared by others when it comes to data mining. By being able to craft your queries, you can leverage the power of data mining more efficiently.

SQL Facilitates Client-Server Access

In a modern environment, data is stored across different servers in multiple locations. Be it on an internal network of servers or in the cloud, and information is rarely accessed from a single point.

If you have SQL knowledge, you can leverage the language to retrieve data from web applications and remote servers. Those skills will allow you to conduct your data management or analysis from a remote location. You also will not be limited to relying solely on data that is stored on-site. The breadth of your data accessibility grows exponentially.

If your work entails maintaining and securing data across different sites and servers, SQL is also beneficial for those instances.

SQL Is Well Suited for Efficient Data Manipulation

Data testing and data modeling are essential to many data analyst positions. The ability to manipulate data efficiently makes SQL ideal for these types of tasks. You also have the added benefit of the dynamic storage capabilities offered by databases running with SQL. Dynamic instances allow you to analyze data across different timeframes. As a result, your testing and modeling can include more in-depth and more detailed structures.

SQL Plays a Key Role in Data Visualization Software

Data visualization is increasingly becoming more important in reporting and transmitting the insights obtained from data analysis. Popular visualization software, such as Tableau, rely on SQL to run the queries required for simple and elaborate reports and dashboards.

SQL knowledge, therefore, will also elevate your skills for practical and detailed visual reporting.

SQL Simplifies Combining Data From Multiple Sources

The more data you can access, the broader your analytical scope and the more profound analysis you can conduct. It is for this reason that combining data from multiple sources is so beneficial.

Without SQL, combining data from multiple sources would be a time consuming and challenging task. Fortunately, through the use of SQL’s UNION operators, combining data becomes less complicated.

Using the SQL UNION syntax, you can identify which fields and databases you wish to combine in your query. This type of SQL knowledge not only makes your job easier but also more precise and detailed. 

Conclusion

Even though SQL has been in existence for decades, its importance as the primary querying language for relational databases has not waivered. If anything, you can say that SQL has solidified and expanded its reputation in data analysis and management.

Therefore, learning SQL is worth it. It improves your abilities and efficiencies when working with data. It also enhances your marketability to potential employers and clients—increasing your compensation.

BEFORE YOU GO: Don’t forget to check out my latest article – 6 Proven Steps To Becoming a Data Scientist [Complete Guide]. We interviewed numerous data science professionals (data scientists, hiring managers, recruiters – you name it) and created this comprehensive guide to help you land that perfect data science job.

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