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Next generation machine learning powered by graph analytics

Machine learning is computationally demanding, not just in terms of processing power but also the underlying graph query language and architecture of the system. We look at how these challenges can be addressed with native graph databases. By Richard Henderson, Solution Architect, TigerGraph EMEA.

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Getting real with AI: 5 areas for stakeholders to activate

There is a lot of excitement about AI, but somehow the reality is not really living up to the hype. By Jelena Stankovic, Content and Communication Lead at SAS.

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Who should be responsible for automation projects?

By James Ewing, Regional Director UK & Ireland, Digital Workforce.

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From Beetle to Bugatti: Lift the bonnet to drive cloud success

By Paul Griffiths, Senior Director, Office of the CTO, Riverbed Technology.

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AIOps: The right Waze to managing IT and driving business success

A common misconception around the customer journey is that it’s a process of A to B. In reality, requirements and circumstances often change at many points along the way – much like a car trip with unexpected traffic and road closures. This is why, as IT requirements get more complex, AI for IT Operations (AIOps) is becoming the future of IT management. By Lee James, CTO, EMEA at Rackspace.

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Practical steps to form your digital transformation strategy

Digital transformation is essentially finding new ways to leverage data within an enterprise, to drive efficiency, revenue and business insight. Now a standard for modern business, digital transformation could be worth $18 trillion in additional business value, according to analyst house IDC. By John Western, Regional Vice President, Europe, LucidWorks.

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Latest Video

How to Adopt an AIOps Strategy: CA Interview with Chris Kline

CA Technologies’ Chris Kline shares how to adopt an AIOps strategy in a DevOps world. Chris shares how AIOps enables a move away from siloed operations management and provides intelligent insights that drives automation and collaboration for continuous improvement. Since AIOps leverages big data, data analytics and machine learning to provide insight and enable a higher level of automation, no longer does IT Ops need to depend extensively on human operators for the management tasks that modern infrastructure and software require.

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