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Data science and machine learning platforms come in a variety of shapes and sizes to meet the ever-changing needs of organizations and their increasingly complex big data environments. Businesses require data solutions that can serve any number of different use cases, and in the case of data science, can range from predictive analytics to natural language processing. There are both small and large providers that offer software to help these companies with both niche and common challenges, though choosing the vendor(s) that are right for your specific environment can be a daunting task. The following providers have recently been named leaders in the 2019 Gartner Magic Quadrant for Data Science and Machine Learning Platforms. The report, which highlights and scores the top products in the industry, features these eight tools as being cornerstones in the space.

The data scientist remains one of the most in-demand jobs, and there are a growing number of data science programs across the country to teach techies the necessary skills. But by the time you gain the skills you need, the job and the data science tools may look much different than they do today. Data scientist skills vary depending on the company, but they generally involve the ability to identify business needs and formulate problem statements based on business requirements. They can prepare the right data for analysis to help meet business needs and assist company leaders to help make decisions, according to Adrian Bowles, industry analyst and founder of Storm Insights, in a Dataversity webinar called "The Disappearing Data Scientist." "They can find the right tools, find the right approach to the data, analyze it in a way that makes sense and interpret that," Bowles said in the webinar.