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How Netflix Uses Big Data to Drive Success

Netflix has over 100 million subscribers and with that comes a wealth of data they can analyze to improve the user experience. Big data has helped Netflix massively in their mission to become the king of stream. Our friends over at FrameYourTV developed the compelling infographic below that highlights Netflix’s use of big data, specifically interesting statistics, how Netflix gathers big data, and how Netflix uses big data.

Interview: Ida Johnsson, Ph.D. Candidate at the Department of Economics at USC

I recently caught up with Ida Johnsson, a Ph.D. Candidate at the Department of Economics at University of Southern California, to discuss how she is actively transitioning to the field of data science. This interview can serve as a compelling example for others wishing to move into the field of data science from other disciplines and explore career opportunities.

Study on AI and the Future of Sales

Whether it’s redefining the world of marketing, finance or customer support, it is no secret that artificial intelligence (AI) is changing the way we work. Sales, as both a function and a profession, is no exception to the sea change. Our friends over at Cien produced a global study: The Future of Sales that reveals how attitudes, perception and behavior of high tech sales professionals is not what is often touted in the media.

5 Misconceptions About Data Science

In this contributed article, technology writer and blogger Kayla Matthews examines the 5 most common misconceptions floating around about data science and what project administrators and business managers need to be aware of. Remember these tips before getting involved, and be sure to do the necessary research. With the right people and knowledge on your side, you’ll be on your way in no time, rocketing to success.

Operationalizing Data Science

In the video presentation below, Joel Horwitz, Vice President, Partnerships, Digital Business Group for IBM Analytics, discusses what it means to “operationalize data science” – basically what it means to harden the ops behind running data science platforms.

Magnetic Swirling Patterns May Offer A New Solution To Data Storage

In this contributed article, technology writer and blogger Kayla Matthews examines a new and potentially game-changing data storage technology involving the use of skyrmions, quasiparticles which have been predicted theoretically and observed experimentally in condensed matter systems. Scientists feel confident about future applications of the skyrmion structure could be used as improvements for conventional data storage devices.

Intermedix Data Scientists Published for Health Care Machine Learning Research

Two of Intermedix’s leading data scientists, Danielle Baghernejad and Lihong Li, have been published in Biomedical Journal of Scientific & Technical Research and Advances in Biotechnology & Microbiology respectively for their pioneering research in machine learning.

Nearly 40% of Data Professionals Spend Half of their Time Prepping Data Rather than Analyzing It

TMMData, creator of flexible data integration and preparation platform Foundation, partnered with the Digital Analytics Association to survey its community about data priorities and challenges. The survey revealed that data access, quality and integration present persistent, interrelated roadblocks to efficient and confident analysis across industries. Most notably, nearly 40% of data professionals (37.5%) spend more than 20 hours per week accessing, blending and preparing data rather than performing actual analysis.

Things You Can Do with a Recurrent Neural Network

In this video presentation from the Linux.conf.au 2015 in Auckland, New Zealand, Douglas Bagnall examines a particularly hot topic in deep learning, namely recurrent neural networks, and all the things you can do with them.

Book Review: Weapons of Math Destruction by Cathy O’Neil

Normally the books I review for insideBIGDATA play the role of cheerleader for our focus on technologies like big data, data science, machine learning, AI and deep learning. They typically promote the notion that utilizing enterprise data assets to their fullest extent will lead to the improvement of people’s lives. But after reading “Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy,” by Cathy O’Neil, I can see that there’s another important perspective that should be considered.