5 enterprise technologies that will shake things up in 2017

Triple A security, the Internet of Things and AR/VR to make their marks

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As 2016 closes, vendors continue to devise distributed applications and platforms based on blockchain technology, and venture capital firms continue to pour money into the effort. More than $1.4 billion has been invested in blockchain technology over the past three years, according to an August report by the World Economic Forum (WEF). More than 90 corporations have joined blockchain development consortia, and more than 2,500 patents have been filed. The WEF predicts that by 2017, 80% of banks will initiate projects that involve distributed ledger technology.

For enterprises interested in exploring how they can use blockchain and distributed ledgers, research firm Gartner recommends starting with limited-scope trials that are aimed at specific problems. Enterprises can start to investigate how distributed networks might improve business processes that are constrained by transaction inefficiency and how technology suppliers might be able to help.

“The challenge for blockchain users and CIOs is to set appropriate expectations among business leaders,” Gartner writes in its 2017 strategic predictions report. “Plan for a reasonable rollout, failure and recovery (especially through 2018); develop realistic proof of concept (POC) use cases; and be agile from an IT and business perspective to follow the best path to success.”

By Ann Bednarz

Machine Learning – the promise of predicting the future

Historically, the challenge for organizations that want to use machine learning and cognitive computing technologies has been that it requires hiring expert data scientists who have spent their careers studying how to crunch data into artificial intelligence algorithms.

In recent years, thanks to the proliferation of public cloud computing platforms, that’s changing. Companies like Amazon Web Services, Google, Microsoft and IBM have all rolled out cloud-based machine learning platforms. “It’s really lowered the barrier quite a bit,” says Sam Charrington, an analyst and blogger who tracks the machine learning market, adding that the technology is being democratized for everyday developers to use in their applications.

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At its most basic level, machine learning is the process of using data to make predictions of future behavior. Most commonly it’s been used in fraud protection (training computers to detect anomalous behavior) and teaching programs to predict future revenues and customer churn. IBM has trained its Watson platform to create sophisticated chatbots for customer interaction and to help healthcare workers provide better care.

It’s still early days for adoption though: A recent study by consultancy Deloitte reported that only 8% of enterprises use machine learening technology today. Allied Market Research predicts the industry is growing at a 33% compound annual growth rate and will reach $13.7 billion by 2020.

“The practice of employing algorithms to parse data, learn from it, and then make a determination … is gathering speed,” reports 451 Researcher Krishna Roy. Consumer adoption of platforms like Amazon’s Echo and Apple’s Siri has seeded this market, but enterprise adoption has been held back by a lack of market education and integration of these systems with existing enterprise platforms. But, she notes that one day this technology could become a “fundamental part of an enterprise's analytics fabric.”

By Brandon Butler

This story, "5 enterprise technologies that will shake things up in 2017" was originally published by Network World.

Copyright © 2016 IDG Communications, Inc.

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