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The Benefits of Having a Data Scientist Career

Our friends over at Simplilearn provided us the infographic below which explores the advantages of the a data science career and shows you the various roles available in this career path, along with projected salaries from around the globe.

Interview: Mary Cameron, Data Scientist at Tophatter

I recently caught up with Mary Cameron, Data Scientist at Tophatter, to get her compelling insights into how Tophatter uses the principles of data science. She also delves into her life as a data scientist at a dynamic and growing company.

Defining the Data Science Landscape

In this contributed article, Manny Bernabe who leads and develops strategic relationships for Uptake’s Data Science team, discusses how it is important to note the distinctions in terminology in the data science landscape. Perhaps most notably, people must be aware of the differences between data science, machine learning and artificial intelligence. The three shouldn’t be used interchangeably due to fundamental differences in their definitions and in what they deliver.

Using Python to Drive New Insights and Innovation from Big Data

In a recent white paper “Management’s Guide – Unlocking the Power of Data Science & Machine Learning with Python,” ActiveState – the Open Source Language Company – provides a summary of Python’s attributes in a number of important areas, as well as considerations for implementing Python to drive new insights and innovation from big data.

Unlocking the Power of Data Science & Machine Learning with Python

The time is now for companies to get started on data science initiatives if they have not already. By addressing these needs early on, data science teams can focus on unlocking the power of their data and driving innovation forward. To learn more download this white paper.

The Rise of the Citizen Data Scientist: Detente in the Era of Data Wars

In this contributed article, Sri Raghavan, Senior Global Product Marketing Manager for Teradata Aster, highlights how the advent of the era of the Citizen Data Scientist is not to be considered a threat to the Data Scientist in the organization. If anything it helps validate the assertions made by Data Scientists about the power of advanced analytics. Having more people like the Citizen Data Scientists attests to the unbridled power of analytics.

How R Powers Data Science at Microsoft

In this video “How R Powers Data Science at Microsoft” from the EARL 2017 conference in San Francisco (June 5-7, 2017), insideBIGDATA’s Managing Editor and resident data scientist Daniel D. Gutierrez chats with Vijay K. Narayanan – Director, Algorithms and Data Science Solutions, Microsoft.

Book Review: The Mathematical Corporation by Josh Sullivan and Angela Zutavern

As a data scientist, I know first hand how today’s enterprise has some catching up to do with engaging the mathematical foundations for capitalizing on an ever-increasing volume of data assets. This is why a new title is so important: “The Mathematical Corporation – Where Machine Intelligence and Human Ingenuity Achieve the Impossible,” by Josh Sullivan and Angela Zutavern. Sullivan and Zutavern are, respectively, senior vice president and vice president of Booz Allen Hamilton.

The Difference Between Data Science and Data Analytics

In this contributed article, tech writer Rick Delgado, examines the differences between the terms: data science and data analytics, where people working in the tech field or other related industries probably hear these terms all the time, often interchangeably. Although they may sound similar, the terms are often quite different and have differing implications for business.

7 Steps From Raw Data to Insight

Data scientists generally ascribe to the “machine learning process” which is seen as a roadmap to follow when working on a data science project. The infographic at the end of this article provides a detailed work flow that it is general enough to encompass pretty much any data science project.