SQL vs Python: Which is better for a career in Data Science?

While there has been much noise about how data science is a great career, aspiring data scientists are still figuring out the usage of SQL vs Python in data science, as to which is a better option to pursue a long. SQL seems limited but worthy enough to understand the basics of data science. Regarding its usage in the field, SQL has not been designed for higher-level manipulations and transformation in data.

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SQL vs Python: Which is better for a career in Data Science?

Whereas, Python is a well-documented and high-level language with a dedicated data analysis library called ‘Pandas’, which makes the choice between SQL and Python a little tricky. Python as well as SQL is important when it comes to learning online data science courses. Here is the basic difference between SQL and Python which will help in clearing confusion between the two.

The online learning mode has been especially beneficial to those who are interested in working in technical fields such as programming. Online education has been a popular go-to mode for a lot of programmers, as it gives the flexibility to study according to their schedule and also because online certification courses are slightly easier on the pockets.

If someone is keen to start their career as a data scientist, there are multiple universities in India providing short-term data science certification courses, SQL certification courses, and Python certification courses. Read on to learn more about the difference between SQL and Python and which is better for a career in Data Science:

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The Difference Between SQL and Python

When it comes to data, it usually comes in multifarious ways. Those days have gone now when data scientists used to store it in a long form. SQL (Structured Query Language), this language specifically used when someone wants to get a quick insight into the data. Whereas Python is considered a quick programming language, and most importantly utilised for data analysis.

Python is known for being quick and efficient and the code is easier. With this explanation, the difference between SQL and Python is quite clear. However, to elaborate on Python vs SQL, mentioned below is the detailed info:

Difference Between SQL and Python

SQL	Python
Easy in learning	Versatile, productive, and high scope of coding
No library options	Library for anything
MySQL, SQLite, PostgreSQL	Python 2 and Python 3
Works on every desktop and mobile-based application	Works on every website on the internet

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SQL vs Python

1. SQL is an open-source relational database management system, it can be easily downloaded and utilised by anyone right from an absolute beginner to a highly experienced data scientist working on some research. Python is a high-level programming language, with usage in web development, data analytics, prototyping, and other similar technical tasks.

This language is built with a high-level data structure compiled with dynamic typing that can easily make the application development process faster. It does not matter if it is built with a high level of technology, but it simultaneously reduces the cost of programme maintenance.

2. SQL has 3 versions MySQL, PostgreSQL, and SQLite whereas Python has 2 types or versions namely Python 2 and Python 3.

3. To start a career in SQL, individuals should have at least a bachelor’s in computer engineering or computer information system or any IT-related major specialisation such as B. Tech/B.E/MCA.

This language requires students to have at least a computer engineering or software engineering degree. Get the basic knowledge of the fundamentals of other programming languages.

4. SQL career paths include SQL Server Database Administration and Development, Business Intelligence professionals, and Data Science will help to climb the successful career path in the SQL journey.

After completing the Python certification course, students have multiple options to get positions such as Python developer, Data analysis, Product manager, and machine learning engineer. Learning Python for data science may set the benchmark and end up getting a job in the largest social media platform: Facebook.

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Python or SQL Which Should I Learn First?

If you are still confused as to which programming language you should learn first between SQL and Python, let us break it down into simpler terms for you. SQL is the standard language for data correction. On the other hand, Python is specifically a well-scripted language built for desktop and mobile-based application development.

According to many industry specialists, they believe that data science with SQL is a very standard language and easy to get started with. It does not mean that Python should not be the first language to start learning Python for a data science career. Python is an advanced language and SQL is the root of it.

Moreover, having a basic knowledge of SQL in data science will easily lead you to the inevitable journey of Python language. Having an embedded understanding of two major programming languages can be a benefit for you to get the data scientist title by the individuals or the company.

Python vs SQL: Which Language to Use First?

Talking about the difference between SQL and Python, in term of SQL, the syntax used in it is simpler than Python and beginners can get comfortable with the language in a quick time.

Python syntax, on the other hand, is a little technical to understand and although beginner-friendly, requires logical thinking to ensure you write error-free code to achieve the right structure. Whereas multiple libraries in the Python language will help you understand a particular project on which you are currently working.

Using SQL vs Python: Case Study

Again, SQL uses quote data from the table within the database. If someone is looking to start their career as a developer, then they should start with SQL because it is a standard language and an easy-to-understand structure makes the developing and coding process even faster. On the other hand, Python is for skilled developers. One of the best things about the Python library is called Pandas. Not the actual pandas though but this panda library is designed for data analysis.

Since this article is about SQL vs Python, there is one thing about Python that should be cleared. Python’s structured data can be fetched using SQL and later all the manipulation part can be done. This process cannot be done by using SQL and data science alone. Therefore, in the end, these two languages are not each other’s enemy. In fact, without one the second language is nothing.

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Salary Package: SQL vs Python

An entry-level SQL developer can expect a salary of about Rs. 289,512 per annum.
With some experience, the level of a candidate can get Rs. 683,480 per annum.
As the experience rises, the salary bar also surmounts the cliff and experienced people will end up getting Rs. 1125,821 per annum.
Python developers (senior-level engineers) are earning more than Rs. 2 million per year.

Python vs SQL: Which One Is Better?

Unlike the ongoing debate on Python vs SQL which is better, when it comes to data science, both SQL vs Python work hand-in-hand rather than one being better than the other. SQL in data science is the standard root to achieve the throne of Python language. Without the help of SQL coding would not be possible for SQL for data science.

However, in this article, we throw a lift on two major programming languages and help students make the right choice and start their careers as data scientists. Because every iteration must start with proper knowledge.

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Conclusion

In the field of data science, there is no strict "SQL vs. Python" competition. Instead, these tools are complementary, and learning both can enhance your data science career prospects. The choice of which one to prioritise first should be based on your specific career goals and the type of data-related tasks you want to focus on. Ultimately, having proficiency in both SQL and Python can make you a well-rounded and versatile data scientist.

Frequently Asked Questions (FAQs)

1. What does SQL stand for? What is the ideal use case for this language?

SQL implies Structured Query Language, whose primary application or use case is to communicate with databases. A domain-specific language is ideally found as part of relational database management systems (RDBMS) & the primary tasks it enables the user to perform include retrieving, updating, inserting, and deleting data from the database.

2. What does a database imply?

A database is an organised record of data that has been created for easy access, storage, and retrieving old as well as new data, and can be accessed via multiple ways.

3. What type of language is Python?

Python is capable of scripting, but in a general sense, it is considered a general-purpose programming language.

4. Is SQL a programming language?

Yes, SQL stands for Structured Query Language and can be used for the manipulation of databases via performing basic CRUD functions. To extract maximum amounts of insights from large quantities of data, a lot of businesses have now turned to SQL as a means to achieve that goal.

5. How should I start learning programming?

Learning programming has become easier with a plethora of online platforms now available, which provide access to some of the best technical and computer science-focused education at super nominal prices.

6. What is the scope for Python programmers in India?

Due to its growing popularity and easy accessibility, Python has widely outraced many of the other languages. The career opportunities associated with the Python language have also grown quite significantly as its popularity has increased by almost 40%.

7. What are some lucrative careers for data science graduates in India?

As a data science graduate, one can form a lucrative career as a Data Analyst, Data Scientist, Data Architect, Machine Learning Engineer, and even an Infrastructure Architect.

8. Which companies in India are hiring data science professionals?

Companies such as Oracle, JP Morgan, and Fractal Analytics among others are actively hiring data science professionals in India. One must also be aware of the python vs SQL differences to stay ahead of the race.