Launched in 2010, Azure rose quickly to become the cloud platform of choice for most organisations around the world. The Microsoft solution has almost one billion users and is trusted by 95% of the Fortune 100. Globally, Azure’s cloud computing market share stands at 21%.
Originally developed to provide access, management, and development of applications and services through global data centres, it has expanded to include more than 200 products with thousands of capabilities from software-as-a-service (SaaS), platform-as-a-service (PaaS) and infrastructure-as-a-service (IaaS) support to AI and machine learning (ML).
Its Azure Machine Learning solutions are instrumental in bringing advanced, business-critical ML models to the mass market at scale. It is used by thousands of data scientists, developers, and engineers to build, deploy, and manage high-quality models faster and more reliably.
Azure Machine Learning is credited with making the complex simple. It allows users to evaluate ML models with reproducible and automated workflows to assess model fairness, explainability, error analysis, causal analysis, model performance, exploratory data analysis and much more – capabilities that were, until its launch, out of reach for all but the largest data science and analytics organisations.
Microsoft is committed to rolling out Azure to as many markets and territories as possible. In 2018, it was the first primary cloud provider to open a facility in Africa, bringing its reach to 54 global regions. A year later, Microsoft announced the establishment of two new cloud regions in the UAE to make it easier for businesses here to further embrace the opportunities of cloud technologies.
Such is its international reach and continued adoption that Azure generated around USD 75bn of Microsoft’s 198bn annual revenues in 2022.
