All large organisations require true data leadership to succeed today. Increasingly, that means using automation tools like AI and machine learning.
The term ‘data leader’ may mean different things to different people, but essentially it’s about how well an individual or an organisation derives value from its data through proactive data analytics.The problem is data volumes are increasing at a phenomenal rate, to the extent that the analytics will increasingly have to be achieved with the help of artificial intelligence and machine learning.
Daniel Gutierrez cites Massimiliano Versace, co-founder and CEO of Neurala, in his article ‘Big Data Industry Predictions for 2017’ for InsideBigData: “More and more companies are applying artificial intelligence and deep learning into their applications, but a unified, standardised engine to facilitate this process has lagged behind.“Today, to insert AI into robots, drones, self-driving cars and other devices, each company needs to reinvent the wheel. In 2017, we will see the emergence of unified AI engines that will eliminate or greatly mitigate these inefficiencies and propel the formation of a mature AI tech supplier industry.”
Why does AI help to solve WAN and data latency issues? Find out more, read the complete article. #YearInReview
Published by Information Age. By-lined to: David Trossell, CEO and CTO of Bridgeworks. Published on 1st June 2017.


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