Big Data and Machine Learning two concepts that are on the lips of everyone today, but no wonder, the profile of data scientist has become one of the most demanded by companies in recent years. According to the report “Professional Big Data: current analysis and future prospects”, job offers have increased by 92% in two years in Spain alone. Companies have realized a reality: the data is their present, but also their future. Data management is no longer a monopoly of large companies to leave the door open for smaller companies decide to give the data the importance they deserve.

We have it clear, as Pat Gelsinger: “Data is the new science. The Big Data answers “; for that reason in this post we want to show you the languages ​​and tools that will continue to be fashionable or that will be a trend in the development of Big Data and Machine Learning in the year 2019.

Python

According to the survey of developers that StackOverflow does every year, Python is one of the 10 most used languages worldwide by professional developers. It also occupies the first position as the language most loved by programmers. Who does not want to learn Python? It is an easy to learn, very clean and readable language with which you can create programs for different devices and platforms such as desktop programs for Mac, Linux or Windows and applications for Android or web pages. Companies like Google, Amazon, Facebook, Instagram, Netflix or Reddit use Python. You still not?

Scikit-learn

It is a free library for Python that uses classification algorithms (defines to which category an object belongs), regression (associates attributes of continuous value to objects) and grouping (groups similar objects in sets); it also operates simultaneously with the NumPy and SciPy libraries. Some companies that have opted for this tool are Spotify , Evernote, Booking.com or change.org. You can read the testimonials of your clients on the Scikit-learn website.

Tableau

It is Bussiness Intelligence software that is used for data analysis. It is a very useful tool for a better and faster decision making in your business as it greatly facilitates the understanding of the data. It is also really intuitive, so the learning curve is not big. Currently this software has more than 50,000 clients from sectors as varied as aeronautics and defense, automotive, education, tourism, government … Some examples of companies that use it are LinkedIn, Adobe, MySQL, Audi AG, Bank of America, Skype, Just Eat or Nike.

D3.js

One of the sectors that is evolving most in terms of scientific software is the visualization of data. Data analysis helps us detect errors or confirm hypotheses that we already had, as well as help us tell a story with this data. D3.js is a JavaScript library used to make data visualizations and add them to a browser using HTML, SGV and CSS. They can be simple, complex and even interactive.

Apache Spark

It is a computer system that is based on Apache Hadoop, it is considered the first open source software that makes distributed programming really accessible to data scientists. Spark is designed to work by processing fragments of data “in memory”, which indicates that data is transferred from hard drives to the system memory, which greatly increases the speed (even a hundred times more sometimes) . Another advantage is that it is easy to install and use and can be used for various business applications. According to the aforementioned StackOverflow survey, Spark is in the TOP 10of the tools most loved by the developers. Some of the companies that use it are Amazon, Microsoft and IBM. What are you waiting for to love him?