SQL: The Essential Skill Every Aspiring Data Scientist Needs

SQL (stands for Structured Query Language) is the standard query language to work and deal with relational databases. It is the core of relational databases and allows you to insert, search, update, and delete database records. It also provides lots of other manipulations and operations, including optimizing and maintenance of databases.

With the help of SQL statements, you can:

• Create new databases
• Create new tables in a database
• Set permissions on different tables
• Execute queries against a database
• Retrieve data from a database
• Insert records in a database
• Update records in a database
• Delete records from a database
• Create stored procedures in a database
• Create views in a database

To understand SQL in a better way, let's use an analogy. If two people want to communicate with each other, they have to use a language that both of them understand. Here, Sarah wants to start a conversation with Jack, and she uses the English language to start the conversation. This language is known to Jack as well. So, they will continue their conversation. But what if one of them didn't understand what the other person said? In this case, there won't be any conversation at all.

Relating to this analogy, if we consider these two people, one as a user and the other as a database, then the language that is used to communicate between these two is called SQL. Similarly, a language has grammar and various rules on how it should be used; even SQL has its own directives.

Here are the advantages that encourage using SQL:

• SQL has well-defined standards
• SQL is easy to learn
• In SQL, we can create multiple views
• SQL queries are portable
• It is an interactive language

Let's talk about why it is important to learn SQL for someone who is interested in data science and pursuing a related career (e.g., a Data Scientist job position) in the industry.

Every day, companies and industries generate and collect lots of data with the huge amounts of data available today. Big data needs a proper set of skills to make sense of it—whether in the medical field, education, industry, sports, etc. These businesses must be able to collect and store data and analyze it to make strategic and informed decisions that will improve their profitability and solve real-life problems. This can be accomplished, and one of the qualifications of a data scientist in this regard is SQL. Here are five reasons why someone interested in working in the field of data science, especially an aspiring data scientist, needs to learn SQL for them to succeed in their data science career:

1. SQL is everywhere

Almost all of the famous names in the tech industry use SQL. Uber, Netflix, and Airbnb are only the most popular examples of a vast range of companies that have employed SQL to facilitate data retrieval and manipulation. While Google, Facebook, Amazon, and other organizations have developed their high-performance DBMS solutions, SQL-skilled programmers would also need to be brought in to help with these projects to get the job done.

2. Easy to learn and use

People applaud SQL for being easy because of its use of declarative statements, unlike complex programming languages, which require learning high-level concepts and rules. Another advantage of SQL is that it uses statements in simple language structure with English words, making them easy to understand and memorize. In fact, if you are new to programming and data science, we suggest SQL as your first pick. You can query data and gain insights with a short syntax.

3. SQL is in demand

It is evident that if you want a data science-related job, your focus should be on the skills employers ask for. Josh Devlin, Data Scientist at Dataquest.io, wrote an article about this and analyzed more than 32,000 data jobs advertised on Indeed to demonstrate the importance of SQL, specifically in data science-related jobs. Here is the result:

As you can see, SQL is the most in-demand skill among all jobs in data, appearing in 42.7% of all job postings. Interestingly, the proportion of data jobs listing SQL seems to be increasing! When Josh performed this same analysis in 2017, SQL was also the most in-demand skill, but it was listed in 35.7% of ads.  

4. Integrates with programming languages

As strong as SQL is for accessing, querying, and manipulating data, some aspects, such as visualization, are limited. As a data scientist, you have to present the data carefully in a way that your team or company understands easily. Programming languages such as Python and R can integrate well with SQL. You can incorporate SQL and Python using libraries like SQLite and PyMySQL to work efficiently with your code package.

5. Manage huge volumes of data

Data science is almost all about coping with plenty of relational-stored data. High-level solutions are needed for managing volumes of data other than the usual spreadsheets, as it becomes infeasible to use them when we have large quantities of data. The best solution here is SQL. Such huge datasets can be effectively handled by SQL because SQL can operate, query, analyze, and gain insights from data pools in a nice way. Although there are more to add to the list, these five reasons will suffice to convince you that SQL is an important skill for an aspiring data scientist.  For a more immersive experience, make sure to take a look at our self-paced training on SQL for Data Science.