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What Happened to Hadoop? And Where Do We Go from Here?

Apache Hadoop emerged on the IT scene in 2006 with the promise to provide organizations with the capability to store an unprecedented volume of data using cheap, commodity hardware. Hadoop facilitated data lakes were accompanied by a number of independent open source compute engines – and on top of that, “open source” meant free! What could go wrong?

How to Adapt to New Technology and Gain a Holistic View of Your Customer

In this special guest feature, Daniel Herdean, CEO of Cognetik, provides four key tips that can help your organization adapt to the new influx of data and ensure you’re providing the best customer experience possible.

How Data Analytics Improve Business Decisions

In this contributed article, Magnolia Potter explains how data analytics have long been seen as a valuable way for businesses to refine their marketing and improve their communication. However, as we learn more about the ways that data can be applied to a business, we’re better understanding the many ways that it can improve business management.

What is Governed, Self-Service Business Intelligence and Why is it Important?

In this contributed article, Ben Bloch, CEO of Bloch Strategy, believes the most effective tools contributing to governed, self-service BI are those that make it easy to migrate data securely and effectively. With this model, organizations can merge self-service BI with governed data sources.

Democratizing AI

In this special guest feature, Saranyan Vigraham, Vice President of Engineering at Petuum, believes that as technology creators, we have an inherent bias in solving challenging technical problems. For democratizing AI, it is also important to solve problems around adoption and the last-mile problem of AI delivery. In a manner similar to e-commerce, an entire ecosystem of players will emerge to tackle this challenge down the road.

“Above the Trend Line” – Your Industry Rumor Central for 8/5/2019

Above the Trend Line: your industry rumor central is a recurring feature of insideBIGDATA. In this column, we present a variety of short time-critical news items grouped by category such as M&A activity, people movements, funding news, financial results, industry alignments, customer wins, rumors and general scuttlebutt floating around the big data, data science and machine learning industries including behind-the-scenes anecdotes and curious buzz.

Pumas-AI Launches Julia Language-Based Software to Advance Drug Development, Patient Care

Pumas-AI – a new company established by University of Maryland School of Pharmacy faculty members Vijay Ivaturi, PhD, assistant professor in the Department of Pharmacy Practice and Science (PPS), and Joga Gobburu, PhD, MBA, professor in PPS – is proud to announce the release of its first cutting-edge software platform for pharmaceutical researchers and clinicians. Known as Pharmaceutical Modeling and Simulation (Pumas), the software was developed through a partnership with experts at Julia Computing.

ThetaRay 4.0 with IntuitiveAI Gives Banks a Powerful New Weapon Against Financial Cybercrime

ThetaRay, a leading provider of AI-based Big Data analytics, announced Version 4.0 of the company’s namesake advanced analytics platform. The update includes major capability upgrades to help global banks detect and prevent financial cybercrime. ThetaRay’s IntuitiveAI solutions replicate the powerful decision-making capabilities of human intuition to detect “unknown unknowns” that cannot be identified by first-generation AI or legacy products.

NuoDB 4.0 Expands Cloud-native and Cloud-agnostic Capabilities of Distributed SQL Database

NuoDB, the distributed SQL database company, unveiled NuoDB 4.0, featuring expanded cloud-native and cloud-agnostic capabilities with support for Kubernetes Operators and Google Cloud and Azure public clouds. This includes the recently announced Kubernetes Operator to simplify and automate database deployments in Red Hat OpenShift.

Free Data Set Archive Helps Researchers Quickly find a Needle in a Haystack

Called the UCR Spatio-temporal Active Repository, or UCR STAR, the archive is made available as a service to the research community to provide easy access to large spatio-temporal data sets through an interactive exploratory interface. Users can search and filter those data sets as if shopping for their research, except that everything is free.