This article first appeared in the Autumn 2015 issue of OnWindows magazine.
Microsoft CEO Satya Nadella took the opportunity to announce the Cortana Analytics Suite – a package of big data and advanced analytics technologies – during the company’s Worldwide Partner Conference opening keynote in July.
The suite, which brings together a host of machine learning, big data storage and processing capabilities behind the likes of Cortana, Bing and so on, will soon be available as a monthly subscription service for businesses.
In essence, the service will enable businesses to analyse their operations, predict future outcomes using machine learning algorithms, improve their decision-making processes with proactive alerting and recommendations, and simplify and automate decision-making when dealing with complex problems. And because the suite integrates with Cortana, Microsoft’s digital personal assistant, people will be able to use voice commands to ask natural-language questions to get the information they’re looking for.
According to Rupesh Khendry, Microsoft’s director of Worldwide Financial Services, digitisation is having a fundamental impact in the financial services industry, creating new opportunities and risks for its constituents. Leveraging data as a key business asset can be a compelling differentiator in garnering insights to rationalise costs, increase revenues, better manage risks and offer end-customers cutting edge solutions and services. The current generation of data management and analytics applications have limited capability in the digital financial services economy. “It’s becoming so important to have state-of-the-art solutions for analysing data,” he says. “With the ability to extract, manage and analyse vast amounts of critical data generated across the institution, as well as exponential unstructured data that needs to be factored in.”
With the Cortana Analytics Suite proposition, Microsoft is bringing to market a comprehensive, world-leading analytics product portfolio in the cloud, hybrid and on-premises. “This includes state of the art machine learning algorithm implementations developed at Microsoft Research and deployed at great scale in Bing, Xbox and Cortana/Windows 10, and Revolution-R which is the most scalable and enterprise-grade cross-platform implementation,” Khendry explains. “Our data and analytics products, coupled with PowerBI and Dynamics CRM, provide the necessary building blocks required for several topical use cases such as fraud detection, cross selling and investment advisory needs. It offers a true end-to-end solution for businesses to enable core analytics scenarios and, ultimately, transform themselves through the power of data – all in a simple, intuitive manner.”
In the following three scenarios, we take a look at how the suite can be put into action.
Based on a market event, a risk manager can analyse the impact to business, run computation models to analyse what-if scenarios and convert that into action thereby driving insight for clients. A risk manager has to factor in a huge amount of data – both structured and unstructured – to predict what will happen to the business on a daily basis. To make smart decisions, they need a holistic view of all lines of dependency that will affect their business.
A product manager’s priority is to understand their clients’ activities and behaviours in order to make the next best product recommendation. Having the ability to analyse client history behaviour and preferences enables better insight and ability to cross sell new products, and have a better chance of determining the right moment to propose a new product or offering.
An investment advisor analyses customer preferences, risk appetite and previous investments based on the customer and social data that is available to them. Based on their client’s portfolio, they are able to make relevant investment recommendations.
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