For some companies, the idea of adopting open-source software doesn’t seem viable. There are many myths about open source, but the truth is that it can facilitate security, be easy to maintain and integrate, and scale to whatever heights you require.

Sign up to stay connected on using Microsoft Azure DevOps with GitHub and Visual Studio, and we can help you unravel the myths and facts about open source.

View: Common myths (and facts) about open source

Digital transformation, accelerated during the pandemic, is redefining the way companies use technology, people, and processes to apply new business models and discover new revenue streams—while striving to meet constant changes in customer expectations surrounding products and services.

The digital transformation consists of five basic steps, starting with the alignment of objectives with business goals.

Emerging technology and revamped processes are important for digital transformation—but nothing is more important than having staff with the right sets of skills. From software engineers to data scientists and UX designers, each plays a key role in the success of digital transformation within a company.

Review the five steps for digital transformation, find real-world examples, and see which pitfalls you’ll need to avoid.

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Thanks to AI, business applications will soon be able to answer complex questions, help users navigate interfaces, and enable cloud vendors to reduce support from personnel to manage their loads. AI is also being used in various software applications to help decision-makers identify and automate repetitive tasks, improving employee productivity. Increased understanding of how to better implement AI in business applications likely will lead to the emergence of new features, such as natural-language processing (NLP), that can help managers interact in more-intuitive ways with AI-powered apps.

In this article, you’ll learn about the innovative features powered by AI and machine learning (ML) that you can expect to see in business applications in the next five years.

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Part of the natural landscape of every business is risk—some level of uncertainty that comes from not knowing how events will unfold as you and your team innovate. However, understanding risk management best practices can help anticipate potential issues and develop a plan.

From securing cloud-based options to identifying cyber threats and other financial crimes, risk management is crucial in building business agility.

Review our latest infographic to learn what you can do to minimize risks and reduce your exposure across key aspects of your business.

View: Risk management best practices

In recent years, the global business landscape has witnessed a significant increase in cloud adoption. This has created significant value over traditional datacenters via greater scalability, cost-efficiency, and other performance improvements. Yet cloud migration requires careful planning. For a migration to be successful, it’s important for the business to come up with a strategy that also covers the end cloud environment, training, and—most importantly—the readiness of workloads and applications.

In this eBook, you’ll discover the key preliminary steps to consider in evaluating a cloud migration, as well as the various approaches for rehosting, refactoring, rearchitecting, and rebuilding your workloads for the cloud. You’ll also learn about some useful tools that you can use to accelerate your migration project and get tips to help you ensure post-migration success by using Microsoft Azure.

View: Cloud migration essentials

For modern organizations to truly take advantage of digital transformation, they need to be able to obtain, process, and extract insights from as much data as possible. This often puts a strain on businesses’ IT departments as they struggle to update legacy software and equipment to better handle the massive amounts of information available. Fortunately, the cloud has allowed businesses to move away from outdated technology and opened new opportunities for innovation.

Subscribe now to learn how the cloud, AI, and the data management capabilities of Microsoft Azure are driving increased efficiency at today’s leading businesses and organizations.

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Industries, customers, and markets change. Even where and how we work is changing rapidly. As are, no doubt, your business strategies, goals, objectives, services, and products. The ability to quickly diversify, scale, and change your business models is a competitive advantage in any market.

Understanding your customers’ opinions, attitudes, and emotional connections to your brand is called brand sentiment. This leading indicator can help inform how you’re doing in terms of your customer experience, product quality, price competitiveness, and loyalty.

Sign up to stay in touch and download the e-book “Essential Key Performance Indicators for Small and Mid-Size Business.” See how easily and accurately you can measure business outcomes from brand sentiment, and let us know when you’re ready to make a change.

View: Essential Key Performance Indicators for Small and Mid-Size Business

What drives a self-driving car? A tremendous flood of data. To make Bertrandt’s Level 4 self-driving car project HARRI a reality, far too much data was needed than could be stored onboard the vehicle itself. It required Microsoft Azure Services to provide access to volumes of mapping data for an autonomous vehicle. Azure DevOps facilitated the efficient coordination of work between developers and ops —and the QA needed to develop such exacting software.

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Data is vital to scientific research. Without the ability to quickly process and analyze large amounts of data, breakthroughs and publications take longer. This increases administrative tasks and can even lead to projects going over budget. To avoid these pitfalls, modern researchers have begun turning to artificial intelligence (AI) and cloud-based technology, which enable the researchers to avoid the time and expense of setting up and configuring servers, leaving them to focus on their scientific goals.

In this video, you’ll see how researchers at Australian National University (ANU) conduct cutting-edge genome research by using Microsoft Azure to commission a data science virtual machine that allows them to instantly process large amounts of data. You’ll also learn how, thanks to the data management capabilities of Azure, ANU is now able to use unprecedented volumes of data and new analytical frameworks to decrease admin time and maximize the university’s research capabilities.

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