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Exploring the Convergence of AI, Data and HPC

The demand for performant and scalable AI solutions has stimulated a convergence of science, algorithm development, and affordable technologies to create a software ecosystem designed to support the data scientist. A special insideHPC report explores how HPC and the data driven AI communities are converging as they are arguably running the same types of data and compute intensive workloads on HPC hardware, be it on a leadership class supercomputer, small institutional cluster, or in the cloud.

Best Practices Report: The Power of Operationalized Analytics

The pace of business continues to increase. And the power of big data and analytics is growing. But it’s not enough to just analyze this data anymore. According to a new TDWI Best Practices Report, sponsored by SAS, businesses also need to take action on this data. Read on to find out how businesses can better operationalize their analytics and derive value from their data. 

Business Analytics are Helping Companies Push the Envelope & Drive Innovation

These days, data and business analytics are the catalysts allowing many companies to push the envelope. A new MITSloan Management Review Research Report, sponsored by SAS, explores analytics as a source of business innovation, as well as how this increased ability to innovate is benefitting a spectrum of industries.

Machine Learning in Finance: Challenges, Successes & Opportunities

AI or machine learning is changing the way industries across the spectrum interact with their customers, as well as develop their processes. And nowhere is this more evident than in the financial business. Download a new insideHPC special report that explores the benefits, challenges and considerations involved with adopting machine learning in finance.

Data Systems Strategies for Today’s Challenges

To address today’s challenges and come up with viable data systems strategies, pharmaceutical companies are looking outside the industry to leverage scientific and technical innovation in other markets.

IoT Analytics – Part 1

Contributed by Daniel D. Gutierrez, Managing Editor of insideBIGDATA, this is the first article in a series focusing on a technology that is rising in importance to enterprise use of big data – IoT Analytics, or the analytical component of the Internet-of-Things. In this first segment, we’ll set the stage for our discussion by providing an overview of the Internet-of-Things. The Internet of Things (IoT) is an emerging theme with wide technical, social, and economic significance. Consumer products, durable goods, automobiles, industrial equipment, utilities, various sensors, and other everyday devices are being combined with Internet connectivity and powerful analytics capabilities that promise to be transformative in terms of the way we live, work, and play.

insideBIGDATA Guide to Retail

In this new insideBIGDATA Guide to Retail, the goal is directed toward line of business leaders in conjunction with enterprise technologists with a focus on the above opportunities for retailers and how Dell can help them get started. The guide also will serve as a resource for retailers that are farther along the big data path and have more advanced technology requirements.

This article is the first in a series that explores a high-level view of how the retail industry has been influenced by big data technologies.

insideBIGDATA Guide to Machine Learning

As the primary facilitator of data science and big data, machine learning has garnered much interest by a broad range of industries as a way to increase value of enterprise data assets. In this article series we’ll examine the principles underlying machine learning based on the R statistical environment.