If you are using R or Python, you might be wondering if it is a good idea to switch to Julia. After all, the language has been growing in popularity. The reality is that it is a powerful language that promises to offer benefits to programmers and researchers in a number of ways. Here is what you need to know about Julia as a data scientist:
You have the option to create classes and types on the fly. This is crucial when you need to define your own custom classes, such as types of cohorts in an analysis, timelines, and even object parameters. If you don’t have the ability to do this, such as with R, you are somewhat limited to how much you can do.
It is important to have dynamic languages in your arsenal as a programmer. Some languages are static. That means they might have a high speed ratio to making computations, but they aren’t able to apply to different APIs or technologies that you might encounter. In today’s world, you are going to need to calculate data from a number of sources. This can include mobile devices, servers, computers, and data center beacons. To track all of this data and put it into a form that is readable requires dynamic abilities, which Julia offers.
Julia may be flexible and easy to use, but it is highly powerful with mathematics. You can compute virtually anything that Python or R provides without much of the hassle. This alone is a reason that it could help you, by speeding up the process it takes to get your results.
The world evolves too fast today for languages to sit still. You need one that has the benefits of constant updating. That way, you can leverage the new techniques, processing efficiencies, and more when you are looking to compute data for your startup, client, or other purposes.
When it comes to data science, it is largely dependent on how good of a language that you are using. When you use R and Python, they can do some amazing things. However, Julia offers some unique advantages that any scientist should consider if they want to take their ability to transform data into key insights for current projects or future planning.