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Top 15 Python Libraries for Data Science in 2017

As Python has gained a lot of traction in the recent years in Data Science industry, we wanted to outline some of its most useful libraries for data scientists and engineers, based on our experience.

21 essential command line interface tools for Data Scientists

In this article, we are going to look at the most convenient tools for quick analysis of data stored in text files (logs, reports, etc.).

6 Top Big Data and Data Science Trends 2017

Recently we stepped in the 2017 year, and it’s time to draw the conclusion about 2016. Our world is depending more and more on the data and information, businesses using data science and machine learning to handle an enormous amount of data. Such things as deep learning and artificial intelligence applications really took off, and we expect those and other important developments to continue. So, let’s have a look at top big data and data science trends for the year 2017.

Open data and smart cities solutions that will change the world

By 2050, 70% of the world’s population is expected to live in urban environments. So smart cities and open data programs will grow and make changes in human life. According to Business Insider Intelligence, by 2020 some 75 per cent of all cars worldwide will be equipped with internet access and associated software, with global revenues from connected services expected to top $152 billion. And other areas of life will develop no less rapidly.

Graph databases use cases

“Big data” grows bigger every year, but today’s enterprise leaders don’t only need to manage larger volumes of data, but they critically need to generate insight from their existing data.