Cloud computing and AI have acquired a reputation for being highly technical and specialised, creating barriers that prevent many researchers from adopting these tools. Below are a few examples of common misconceptions or myths about cloud computing.
Who is Azure for... Introduction
Who can benefit from Azure?
Myths about Azure and Cloud Computing
"Azure is only for AI specialists"
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Azure offers tools for all expertise levels, from no-code interfaces to advanced development environments. If you have little to no experience you can use the pre-built models with a graphical interface to see if they work with your data. If successful, you know to go further into the topic and gain more control.
"You need coding experience"
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Many Azure services feature intuitive visual interfaces requiring zero code. Drag-and-drop workflows and guided processes make the AI models accessible to all researchers. While coding knowledge can be helpful for more advanced customisation, it's absolutely not required to get started and achieve meaningful results with your research data. Check out automated Machine Learning and the Custom vision section for examples of no-code tools.
"It's only valuable for big data projects"
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Azure tools benefit datasets of all sizes. Whether automating analysis of a few hundred microscopy images or extracting insights from decades of field notes, the platforms scale to your needs. Sometimes the greatest time savings come from automating routine tasks with small datasets, giving you more time to focus on interpretation and scientific discovery.
"Cloud computing is too expensive"
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Azure's pay-as-you-go model eliminates expensive hardware purchases and allows you to try out and find the computational power you need, in small periods. Academic institutions typically have special pricing arrangements, and students/researchers can access free credits to get started. Many tools and services have free tier availability for preliminary research.
"My data won't be secure"
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Azure provides comprehensive security controls, compliance certifications, and data sovereignty options. You maintain complete control over who accesses your research data. Azure meets international standards for data protection, including GDPR compliance, and offers specific tools for managing sensitive research data.
Microsoft Azure should provide at all times excellent stepping stones for you to gradually build up your confidence in making decisions around using AI, without worrying about software configuration, expense, or security concerns.