Top 5 Programming Languages For Data Science
Fun Fact: Over the last two years alone 90 percent of the data in the world was generated.…
The term ‘data science’ has been buzzing around the technology world for the last few years. Now every business wants to employ data scientists.
So what’s the hype about data science? In today’s competitive technology market, numerous data of various kinds are being generated each day. The amount of data we produce every day is tremendous. There are 2.5 quintillion bytes of data created each day at our current pace, but that pace is only accelerating.
With that much digital data available, they play an important role in reshaping industries and assists decision-makers in their work. So it became a standard to extract insights from massive amounts of data using various scientific approaches, processes and algorithms. This what data science is all about.
What Is Data Science?
According to Wikipedia:
Data science is an interdisciplinary academic field that uses statistics, scientific computing, scientific methods, processes, algorithms and systems to extract or extrapolate knowledge and insights from noisy, structured, and unstructured data.
Data science is a hot topic these days. If you are considering to look for a job in data science field, getting started can be a bit daunting. You have to chisel up your programming skills if you want to succeed as data science involves high coding expertise.
The need for a data scientist is expanding along with the value of data. Data scientists are who uses mathematical and statistical techniques to manipulate, analyze and extract information from data.
There are many programming languages that are helpful, but we need languages that offer high productivity and performance to process large amounts of data.
Top programming languages for data science
| Languages | Best Used For | Pros | Cons |
|---|---|---|---|
| Python | Python is best used for automation. Automating tasks is extremely valuable in data science and will ultimately save you a lot of time, and provide valuable data. | -Endless support -Open source tools for visualization and machine learning | -Relatively slow for computation |
| JavaScript | JavaScript is best used for web development. | -Good for creating visualizations | -Doesn’t have the range of data science packages and built in functionality |
| Java | Java is best used for creating complete applications. It makes building mobile or desktop applications incredibly easy. | -Build more maintainable and scalable software -Easily portable has a true garbage collection | -Not as flexible and friendly -Networking opportunities and support are less easy to come by. |
| R | R is best used in the world of data science. It is especially powerful when performing statistical operations. | -Open-source -Large amount of support -Multiple packages quality plotting and graphing | -Lacks basic security |
| SQL | SQL is the standard and most widely used programming languages for relational databases | -Easy to code | -Difficult interface -Some versions of SQL can be very costly |
Conclusion
If you wish to became a data scientist, learn the correct programming language for a smooth and successful career. Data Scientists must upskill themselves and have to be up-to date about changing industry standards. The above compiled a list of top programming languages will surely give a boost your career.