Tools for Data Science

The following is the movement in just 3 years of the players which got their position in the well known, Gartner Magic Quadrant.

Gartner keeps changing the names for this report (and by implication the market segment) - the latest 2018 version, published Feb 23, 2018, is called "Magic Quadrant for Data Science and Machine-Learning Platforms" (with an old-fashioned dash between Machine and Learning). In 2017 it was "MQ for Data Science Platforms", and in 2014-2016 it was "MQ for Advanced Analytics Platforms". This change reflects the rapid changes in the industry, both in terms of content and capabilities. and the evolving branding which reflects the growth of AI and Machine Learning -  Gregory Piatetsky

Python and R are not a part of this report. However, these are important and play an increasingly important role in data science market.Data science and machine-learning platforms enable organizations to take an end-to-end approach to building and deploying data science models. This Magic Quadrant evaluates 16 vendors to help you identify the right one for your organization's needs.

It's easy to get carried away with new technologies such as machine learning and artificial intelligence - however, traditional forms of analytics and business intelligence remain a crucial part of how organizations are run today, and this is unlikely to change in the near future. This is a good webinar to go over the Gartner Magic Quadrant.

What tools are you planning to master later in your career? Why would you choose those? Need help deciding on what relevant PhD thesis topic should you choose?

Educate yourself to be ready for the future. Contact Us for relevant and right directions to help you with M Tech or PhD thesis guidance. We’re based in Chandigarh. We have online classes as well to offer services across India.

Or call us on +91–9023469578 / +91–7508793518

Post a Comment

Make sure you enter the(*)required information where indicate.HTML code is not allowed