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Top 7 Reasons Data Scientists Should Know Java Programming Language

Blog: Think Data Analytics Blog

Java is the #1 programming language for Big Data, Analytics, DevOps, and AI. It is consistently the first choice for developers working with data. The platform-independent programming language is robust, scalable, and reliable. Finding uses in data science, Java development services are in high demand among companies that are focusing on utilizing data for enterprise expansion and growth.

21% of data scientists use Java application development on a regular basis. It is the 5th most popular programming language for data, just after Python, SQL, R, and C/C++. While many developers use Python and R for Machine Learning applications, knowing Java is essential for data scientists as well. It has great uses in Machine Learning and Artificial Intelligence. 

Java is mostly used to put Machine Learning models into production. Even though Python is the most popular programming language for Machine Learning, it cannot easily engage in model production and is slow when it comes to execution. Therefore, Java can be advantageous to data scientists who frequently execute ML models. 

This article will address the top 7 reasons why data scientists should know Java. It will highlight how Java software development services enable enterprises and startups to take advantage of its versatility in Machine Learning development. 

7 reasons Java is Good for Data Science 

Some of the world’s best companies use Java, including Uber, Spotify, Airbnb, Wikipedia Search and more. It offers a plethora of services that developers can build using different IDEs and integrate Machine Learning models in them. Data Science is one field that requires a lot of heavy lifting, which means it needs a programming language that survives that. Java programmers build the most complex applications with ease.

Here are 7 reasons why data scientists should know Java application development – 

Wrapping Up

Java is an amazing programming language for data scientists due to its scalability, versatility, and flexibility. There are a lot of features and tools that they can use to build Machine Learning models and deploy them with ease. Any Java development company can create Machine Learning solutions by using the tools & technologies that the programming language has to offer.

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