This week, all eyes were on the Consumer Electronics Show (CES) in Vegas, which is widely respected (and reviled) as the barometer for the consumer electronics industry for the year ahead. Our colleagues at Gigaom spent the week reporting from the Las Vegas Convention Center; full CES coverage is here, including one of the most colorful press conferences we’ve ever covered, courtesy of T-Mobile’s John Legere. Meanwhile, our analysts at Gigaom Research have their own barometers for the year ahead; this week, some of the most popular Gigaom Research reads include reports on what’s next for the cloud, the future of collaboration through videoconferencing, and the next stage for data analytics.
First, in “Top 10 cloud trends for 2014,” Janakiram MSV takes a quick look back at breakthroughs and disappointments in cloud computing in 2013 before diving in to the top 10 developments that Gigaom Research’s cloud analysts predict for the year ahead. With big shifts ahead for both public and hybrid clouds, Janakiram also takes a look at what’s in store for the cloud and the internet of things, as well as next steps for OpenStack, SDN, and more.
Next, in “Why videoconferencing is critical to business collaboration,” David Coleman looks at the role of collaboration between geographically distributed businesses and teams, and the role that video conferencing technology plays in these interactions. Coleman looks specifically at cloud-based video conferencing, which provides “high fidelity and the ability to connect seamlessly to any video end point,” as well as a more affordable alternative to single-vendor, hardware-based systems. Noting that “87% of remote users feel more connected to their team and process when using videoconferencing,” Coleman takes a look at use cases from the education, finance, health and construction sectors, and provides a list of minimum requirements (and added features) for IT managers and technology buyers to consider when selecting videoconferencing systems.
Last, in “Applying big data analytics to human-generated data,” Paul Miller looks at a emerging opportunity in the analytics industry: analyzing human-generated data, such as email messages, texts and documents. While the cost of mining this data can be significant, unstructured human-generated data (and the metadata associated with it) can provide valuable insights and information, such as “key intellectual property, operating procedures, and the plans and strategies that shape future development.” Miller analyzes the challenges and the benefits of gathering and analyzing human-generated data, how to mitigate risks, and use cases such as natural language processing.
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