Across Gartner’s Magic Quadrants for Cloud Storage Services, Application Platform as a service, and Cloud Infrastructure as a service, Microsoft is clearly the leading vendor. Azure provides users with a growing collection of integrated cloud services that enable productivity with a host of features, tools, templates, and managed services.
For developers and IT professionals, Azure presents an open and flexible platform where a broad range of existing skills or environments, and familiar technologies, are supported easily. Microsoft is offering organizations more flexibility and productivity via more IT options with less complexity and cost, scalability with a pay-as-you-go service, overlaid with an industry-leading commitment to data protection and privacy.
Microsoft built Azure to be the enterprise data center of the future, using PaaS, IaaS, and SaaS features to support the computing, storage, security, and server configurations required by most businesses. With Azure, building and maintaining IoT is no longer as difficult for businesses because more intelligent reporting can now be done with Big Data, and then used to answer difficult questions businesses will continue to face in the future.
In this post, we hope to briefly explain Azure Machine Learning, and how its amazing features can be used to help your business consume or develop business applications of the future.
Azure Machine Learning
Machine Learning helps create smarter applications by examining large amounts of data and capturing patterns, recognizable from generated codes, that help make better predictions. Using statistical techniques to identify the best pattern to solving a defined problem, the machine learning process generates a code, otherwise referred to as a model, that can be called by applications when problem solving.
Azure Machine Learning solutions provide powerful cloud-based tools for modelling predictive analytics through a fully managed service that can be easily deployed as ready-to-consume web services. Models can be built from algorithm modules trained with data that is either labelled or not, then evaluated using data with known outcomes to determine if the model predicts accurately.
In layman’s terms, Machine Learning basically involves computers looking at lots of existing code to help create new code that solves new problems.
The Azure Marketplace
With Azure Machine Learning, you can create a training experiment using Azure Machine Learning Studio, convert it to a predictive experiment, and then deploy it as a web service, so that users can send data to your model and receive its predictions. Azure Marketplace provides a platform where you can publish paid or free Azure Machine Learning web services for developers, or external customers, to consume in their applications.
This is also an online store for thousands of certified software applications, developer services, and data which can be easily searched and deployed, for simplifying the development and management of business applications. It combines Microsoft Azure partner ecosystems into a single unified platform with a wide range of solutions to enhance productivity and performance, for both customers and partners.
The Azure platform is such a powerful way of easily creating APIs, and beginning to process data quickly, that both data scientists and customers can publish APIs with just a few clicks. Some very cool APIs include the text analytics API for sentimental analysis and keyword extraction on unstructured text, recommendation APIs for recommending items to increase conversion rates on your website, and many more.
With Azure API Management, you can launch a full-fledged API program based on any backend enabling businesses to easily secure mobile infrastructure, enable ISV partner ecosystems, and run internal API programs.
Speaking of Azure APIs, Sharegate's Insane Mode for Office 365 Migration actually uses one. These things sure are powerful!
Who doesn’t want to better understand their data? With the Cortana Analytics Suite, transforming your data into intelligent actions is now easy. Fully managed, it can really help businesses enhance their own applications. Business decisions can now be made quickly, and with more accuracy, by benefiting from predictive analytics, prescriptive analytics, and automated decision making for complex scenarios.
Cortana Analytics can help your business enable predictive and preventive maintenance to help eliminate downtime, and increase customer satisfaction by connecting more effectively to your data and customers.
According to Keith Mayer of Microsoft, Azure is:
“Really an extension of Office 365 that allows you to run customized business applications, and develop custom web applications, that easily integrate with SharePoint online. It extends Office 365 with custom mobile application support, and also extends the Office 365 Active Directory infrastructure, providing single sign-on access to a host of SaaS applications outside the Microsoft ecosystem.”
So if we look ahead, Azure and IoT will certainly play a big part in the future. The ability to easily integrate and build new solutions through enhanced Business Intelligence using large amounts of IoT data - both predictive and real-time analytics - is something that will drive innovation, and create some exciting new applications.
Tell me, do you use any kind of Azure Machine Learning, and if so what for?