As more businesses adopt cloud services at a greater scale, the need to leverage AI and automation for cloud migration success has increased. This article explores the move to the cloud, how businesses can leverage AI and automation to support this, while also looking at what success looks like in a cloud migration. Businesses are moving critical workloads to the cloud at an accelerated rate. This trend was sped up during the pandemic, but the dial was always moving in this direction. The reason for this, according to Rob Duffy – head of solution development at Cloudreach – is that the move to the cloud "allows businesses to be more agile and respond faster to changing customer conditions and customer expectations."

As machine learning disrupts more and more industries, it has demonstrated its potential to reduce time spent by employees on manual tasks. However, training machine learning models can take months to achieve, creating excessive costs. With this in mind, AWS vice-president of machine learning, Swami Sivasubramanian used his keynote speech at AWS re:Invent to announce new tools that aim to speed up operations and save costs. Sivasubramanian went through five tenets for machine learning that AWS observes, which acted as vessels for further explanations of use cases for the new tools. Firstly, Sivasubramanian explained the importance of providing firm foundations, vital for freedom of creativity.

While the prospect of deriving reliable insight with machine learning (ML) and AI-driven data analytics may seem overwhelming, it doesn't have to be, says Cloudreach Chief Technologist, John Loughlin. In a June 2020 webinar, we discussed how to approach data analytics with pragmatism and confidence using Google Cloud Data (GCD) Services. Here we'll recap that advice, providing an overview of how businesses can implement the building blocks of becoming a data-driven organization using GCD Services. Keep in mind that the overarching goal – to enable the analysis that opens the door to better business decisions – rests on the core values of security and governance, which together provide the context for making effective use of technology. Safeguarding data is fundamental to your program and to doing right by your stakeholders.