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News, reviews and feature articles on companies that are changing how organizations leverage massive volumes of data

Field Report: TIBCO NOW 2018

I was pleased to be on hand for the 2018 edition of the TIBCO NOW “Innovation at the Edge” conference in Las Vegas on September 4-6. This was my 1st time covering the show for insideBIGDATA, and I was eager to get the pulse of the event because you can tell a lot about the state of a company by attending their global user conference. I wasn’t disappointed!

Combining the Benefits of Commercial & Open Analytics

A new e-book explores how organizations in many industries are using open source analytics and SAS, getting the most from both, and what role SAS plays throughout the analytics life cycle.

Improve Your Business with Modern Analytics Infrastructure

A new report from SAS explores how a modern analytics infrastructure and IT department can help you increase productivity, maintain the highest data quality through a standard data governance model, and make critical decisions faster and with more confidence.

Tableau Enables Developers to Extend Functionality with New Extensions API in 2018.2 Release

Tableau Software, Inc. (NYSE: DATA), a leading analytics platform, today announced the general availability of Tableau 2018.2. This release introduces a new Extensions API that enables customers to drag and drop third party functionality directly into a dashboard. Publicly available extensions can be found in the new Extension Gallery at tableau.com/extensions.

Movies, Neural Networks Boost AI Language Skills

When we discuss about artificial intelligence (AI), how are machines learning? What kinds of projects feed into greater understanding? For our friends over at IBM, one surprising answer is movies. To build smarter AI systems, IBM researchers are using movie plots and neural networks to explore new ways of enhancing the language understanding capabilities of AI models.

IoT Feeds Data Stream to AI Application Converge for Real-time, Sideline Insights

In this contributed article, Jason Mann, Vice President of Internet of Things (IoT) at SAS, discusses how IoT creates enormous streaming data volumes, much of it unused or lost. Data lost is opportunity missed. The key to unlocking the value of IoT data is with AI applications that self-learn and automate actions. AI applications – created with analytics and using real-time IoT data – can reveal new business opportunities long before the competition wakes up.

Interview: Jamie Engesser, VP Product Mangement at Hortonworks

I recently caught up with Jamie Engesser, VP Product Mangement at Hortonworks during the company’s DataWorks Summit 2018 conference in San Jose, California, to get an update on his company’s direction and his sense for the pulse of the big data industry.

Databricks Partners with RStudio To Increase Productivity of Data Science Teams

Databricks, a leader in unified analytics and founded by the original creators of Apache Spark™, announced a partnership with RStudio, providers of a free and open-source integrated development environment for R, to increase the productivity of data science teams. The partnership will allow the two companies to seamlessly integrate Databricks’ Unified Analytics Platform with the RStudio Server, simplifying R programming on big data.

Field Report: DataWorks Summit 2018

In this field report I wanted to give you a sense for what the vendor ecosystem was saying at DataWorks Summit, their corporate message if you will. Each company had a somewhat different slant of course which aligned with their products and services, but there was also a lot of commonality. Most everyone had some tie into the industry’s current buzz – AI, machine learning and deep learning. This was perfect for me as a practicing data scientist myself. Let’s get started with some vendor snapshots …

Advancements in Dynamic and Efficient Deep Learning Systems

We’re seeing much hype in the marketplace about the potential of AI, especially with respect to computer vision systems and its ability accelerate the development of everything from self-driving cars to autonomous robots. To create more dynamic and efficient deep learning systems, that don’t compromise accuracy, IBM Research is exploring new and novel computer vision techniques from both a hardware and software angle.