Types of Programming Languages for Data Scientist

Data science is paramount in aiding businesses in getting deeper insights into their information and customers’ preferences. Businesses can make the right decisions and implement effective strategies with the right data science techniques. To achieve the results and witness success, using the best programming languages for data scientists is paramount. The scientists use programming languages like general-purpose programming languages, languages for application and database design, and specialized languages for statistical analysis and visualization based on the project requirements. But today when the market is flooded with so many programming languages, choosing the right one for data science becomes an overwhelming task.

So, to help you come out of this dilemma, we have discussed some of the top data science programming languages, their applications, and their usage in the field.

How is Programming Useful in Data Science?

In data science, coding language is used across various verticals enabling data scientists to pull data from multiple datasets, clean and analyze the same. The decision to choose the best programming language depends on your role as a Data scientist, specific project goals, and how much experience you have.

Python

Python is ranked among the most popular programming languages for data scientists, and Python’s syntax is easy to follow and write. This enables data scientists with a basic coding background as well to learn Python and start deploying the same quickly. Python being an open-source, general-purpose programming language is not only beneficial in the data science industry but is widely used in other domains such as web development and video game development. Python is capable of performing various kinds of operations; from data preprocessing to visualization to statistical analysis, it is used across many verticals.

R

R is also an ideal option for aspiring data scientists. Frequently being named as the main competitor of Python, knowing R language is an important step to breaking into the field. R is an open-source, domain-specific language, and is purposefully designed for data science. This programming language is the perfect language for data manipulation, processing and visualization, statistical computing, and machine learning. R supports various types of data, and it is useful for Data scientists responsible for cleansing and data wrangling.

SQL

Structured Query Language or SQL is a domain-specific language allowing data scientists to communicate edit and extract data from the existing databases. Having a detailed knowledge of databases and SQL is important as it allows the experts to work with various relational databases such as SQLite, MySQL, and PostgreSQL.  SQL also integrates easily with other languages like Python and R, letting Data scientists use SQL to query specific data from a database followed by Python or R to perform a deeper analysis of the retrieved data.

Java

Java is another famous programming language for data scientists. It is an open-source, object-oriented language, known for its first-class performance and efficiency. Java language is used in software applications and for website designing. In the last few years, Java language has gained a prominent role in the data science industry mainly due to the Java Virtual Machines that provide a solid and efficient framework for popular big data tools.

The data scientists use Java for importing and exporting data, cleaning data, text analytics, statistical analysis, machine- and deep learning, and for data visualization as well.

Julia

This programming language, despite being one of the youngest languages, has already gained wider popularity in the numerical computing world. It is a highly effective tool as compared to other languages used for data analysis. Julia despite having a smaller community, still it is one of the most promising languages for data scientists.  High speed, clear syntax, and versatility make Julia an ideal option. Because Julia is a high-level and general-purpose language, Data scientists can write and quickly deploy executable code using Julia.

Scala

Scala has recently become one of the best programming languages for data scientists machine learning and big data. Launched in 2004, Scala is a multi-paradigmatic language explicitly designed to be clearer and an ideal alternative to Java. Scala also runs on the Java Virtual Machine, allowing interoperability with Java. It makes it an ideal language for distributed big data projects. Scala is a highly functional language and is written with fewer lines of code. Many organizations use Scala because of its scalability.

#C/C++

They are popular programming languages and are used across various verticals. Among them, C is a general-purpose language and C++ is an object-oriented programming language. Both of them are helpful for data scientists. C and C++ are two of the common languages useful when it comes to addressing computationally intensive data science tasks. Both of these languages are quite fast compared to other programming languages. This makes them perfect for developers developing big data and machine learning applications.

Many popular machine learning libraries like PyTorch and TensorFlow use C++.

JavaScript

It is a multiparadigm, versatile language, known for building rich and highly interactive web pages. So, the data science industry also uses this language. This language supports several libraries for machine learning and deep learning including TensorFlow and Keras. So developers use it for front-end and back-end development.

Unlock the Power of Data with Kodehash’s Data-Driven Excellence

Choosing the right programming language for data scientists is paramount for the success of your project. Use Kodehash’s Data Science expertise to explore, predict, optimize, and manage your data. Our streamlined process ensures data security.

Have a look at how Kodehash can help you:

• Explore Kodehash’s cutting-edge data science services and solutions customized as per your business needs.
• Book a consultation with our experienced and certified data scientists and software engineers and shortlist the best programming language.
• Our data scientists have experience in AI, Computer Vision, Image Recognition, ML, Deep Learning, etc.
• We have 10+ years of experience in this domain and use the right programming language to deliver outstanding results.

So choosing the right programming languages for data scientists is essential for any successful app. A wrong choice can result in poor performance, poor loading speeds or worsen the situation with data breach security.

To avoid such problems, reach out to the experts at Kodehash Technologies. We will help you embark on your software development journey and build outstanding applications. Contact us to learn more on which programming language fits your business.