In the second of our five-part series on how your business can leverage the benefits of the Microsoft Azure cloud, we examine how Azure data and AI can be used to make smarter and faster decisions to further your business.
One of the best things about Microsoft Azure is that it not only replaces what you could already do with on-premises infrastructure, but it puts you on the cutting edge of what businesses can achieve in the Cloud.
It seems like talk about AI and big data analytics is everywhere these days. And if you don’t already use these technologies, the idea of using artificial intelligence (AI) to help your business work smarter might sound like science fiction. Not so; Azure is packed with features that help you harness these technologies and gain an advantage over your competitors.
What does this mean in practice? Here are some of the possibilities Azure data and AI can open up for you.
Make smarter decisions with Azure Machine Learning Studio
Typically, businesses use sales data, data on their people, expenditure logs and other information to make sense of their past performance. But what if you could use that same data to predict what you should do next?
Azure Machine Learning Studio is a web-based tool that lets anyone experienced with working with data get started with artificial intelligence. If they have no coding experience, the software has automated machine learning models and simple, drag-and-drop interface options.
These options, coupled with tutorials and workflow examples help make Machine Learning Studio easier to get to grips with.
Here are some of the ways companies have used Azure machine learning capabilities:
- Retailers choosing new store locations by combining factors like sales data, consumer behaviour, workforce availability and socioeconomic data
- Airlines optimising air travel ticket prices based on automated predictions of flight demand across different holiday period and global events
- Businesses of all kinds predicting sales performance for months in advance based on historical analysis, combined with environmental factors, helping to optimise their use of marketing and sales resources at the right time
It is important to note that to make the most of Azure Machine Learning Studio, you will need team members who are already comfortable working with and analysing data. But what you won’t need is a huge investment in software engineers to build AI tools for you. Your data analysts can do it all themselves.
It’s all about spending less time manually trying to make sense of data and more time developing smarter strategies based on the data you’ve organically created over the years.
Azure offers many compelling data-related services that let us ingest data from internal and external sources, transform this data and perform advanced analytics.
This new data can then be presented back to the relevant stakeholders through easy-to-consume dashboards such as Microsoft Power BI.
Understand your business better with Power BI
You don’t need to be a developer or data scientist to make use of Azure’s AI capabilities. Microsoft Power BI is aimed at a wider range of users than Azure Machine Learning Studio.
Power BI turns your raw data into dashboards and reports that provide actionable insights, helping you make smarter strategic and day-to-day decisions.
In the last few years, Microsoft has been busy enhancing Power BI with artificial intelligence features that let anyone – not just data scientists – extract meaningful findings from their data.
Built on the same core technology that powers Azure Machine Learning Studio, it is simpler to use.
Some of the ways you can use AI in Power BI include:
- Making sense of important business metrics with the ‘key influencers’ feature. This analyses data to find out which factors drive particular outcomes. Why are certain customers scoring you below average in satisfaction surveys? Rather than manually sift through the data, this tool can help highlight issues you need to address.
- Combining Power BI with the Azure Cognitive Services API to carry out deep analysis of text. This can highlight important phrases, help you understand customer sentiment, identify mentions of brands and more, through Azure’s natural language processing abilities.
Training AI to work smarter on your behalf. You can build machine learning models in Power BI no matter how much experience you have of working with data. Get to grips with the Automated Machine Learning feature and you’ll have data bending to your will.
Bring the power of AI to your apps
Whether you build apps for customers or for internal use, Azure lets your software take advantage of advanced AI models used by some of Microsoft’s best-known products like Microsoft 365, Xbox and Bing.
You’ll be able to offer smarter, more predictive services to your users, based on the work of some of the world’s best AI engineers.
The features you can build into your apps include:
- Speech-to-text and text-to-speech – Build easier-to-use interfaces and powerful transcription tools
- Automatic speech and text translation – Simplify inter-language communication and improve your understanding of what customers and others say about you around the world
- Automated analysis of images and video – Build content moderation tools and other software that makes sense of visual media
- Face recognition – Build software for security, research and more that analyses human faces
- Language understanding capabilities – Build chatbots and voice assistants that understand your users’ natural conversational flow
It’s worth noting that some AI features aren’t available in some parts of the world, but most are widely available.
Search smarter with Azure cognitive search
It’s a common problem; you have a mountain of data but knowing exactly what you want from it is incredibly difficult. Whether for internal use or for your customers, having powerful search tools on hand can open all sorts of new possibilities by surfacing more of the right kind of information.
Azure Cognitive Search lets you harness AI for analysing text, images and video, audio and more.
Some of the ways you could use these capabilities include:
- Giving your users more accurate search results – With the help of deep learning models that understand not just keywords, but the exact information a user is trying to find
- Transforming an archive of scanned paper documents – Into structured, searchable data
- Making audio from recordings of meetings and events searchable – So you can discover exactly who said what and when
Given the breadth of possibilities available with Azure data and AI, this article has only scratched the surface. But hopefully it’s inspired you to dig deeper and explore the ways you can make more use of the data you already have to drive your business performance to the next level.