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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.

Outlook on Artificial Intelligence in the Enterprise 2018

Narrative Science, a leader in Advanced Natural Language Generation (Advanced NLG) for the enterprise, announced the availability of its third annual research report, “Outlook on Artificial Intelligence in the Enterprise 2018.” In partnership with the National Business Research Institute (NBRI), Narrative Science surveyed business executives from a wide array of functions, including business intelligence, finance, and product management, to understand the use, value, and impact of AI throughout their businesses.

Implications of Big Data Evolution on Marketing

In this special guest feature, Jordan Cardonick, Director of Media Analytics at Merkle, discusses the common pitfalls and missteps that companies fall into when trying to democratize data and insights for their company. It isn’t just about what data you have access to, but how do you ensure it is effectively communicated and embraced and not just how to use it to create a chart, graph or model.

New SAS® Data Preparation Gets Big Data Ready for Analysis

With 2.5 quintillion bytes of data being created every day, organizations need better ways to prepare it for analysis. Analytics leader SAS is now offering SAS® Data Preparation to provide analytics professionals and business users an interactive, real-time self-service application that will ease the burden of readying data for analysis.

Hadoop 3.0 Perspectives by Hortonwork’s Hadoop YARN & MapReduce Development Lead, Vinod Kumar Vavilapalli

In the Q&A below, , Hortonwork’s Hadoop YARN & MapReduce Development Lead, Vinod Kumar Vavilapalli, offers his perspectives on the recent release of Hadoop 3.0, the latest version of the Open Source software framework for reliable, scalable, distributed computing.

Sentience: Reimagine What’s Next for Big Data in the era of AI

In this special guest feature, Oliver Ratzesberger, Chief Product Officer for Teradata, discusses his new book titled “The Sentient Enterprise” which highlights the future of business decision-making, analytics, AI and deep learning.

Quadcopter Navigation in the Forest using Deep Neural Networks

In the video presentation below, a group of deep learning researchers study the problem of perceiving forest or mountain trails from a single monocular image acquired from the viewpoint of a robot traveling on the trail itself. Previous literature focused on trail segmentation, and used low-level features such as image saliency or appearance contrast; the team proposes a different approach based on a Deep Neural Network used as a supervised image classifier.

Data Governance: Lessons Learned from the Front Lines

In this contributed article, Ken Arnold is Analytics Manager at Covenant HealthCare, says there’s no question that a strong data analytics foundation is critical in today’s healthcare ecosystem. If your organization is considering adopting a data governance capability to support your analytics efforts, keep these best practices in mind to ensure that your data is consistent, accurate and trusted across the entire organization.

How Self-Learning Programs Help Businesses Save Time and Money

In this contributed article, technology writer and blogger Kayla Matthews points out that AI and machine learning can learn from experiences without constant input from programmers, and as a result businesses are increasingly looking for ways to use them to make their operations more efficient and cost-effective. Here is a shortlist of some ways that self-learning programs help businesses save time and money.

Pay Attention to Spatial Data, It Is the Next Frontier

In this special guest feature, Madhusudan Therani, CTO at Near, points out that with an almost endless list of sources – including map and satellite data, catchment areas, service points, building and customer locations, land use data, urban data, and communication pathways – spatial data is a valuable global commodity which comes in many forms. So why do businesses need to process spatial data and what are some of the challenges they face in doing so at scale?