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Whether you have responsibilities in software development, devops, systems, clouds, test automation, site reliability, leading scrum teams, infosec, or other information technology areas, you’ll have increasing opportunities and requirements to work with data, analytics, and machine learning.
Tech Spotlight: Analytics
How to choose a data analytics platform (InfoWorld)
6 best practices for business data visualization (Computerworld)
Healthcare analytics: 4 success stories (CIO)
SD-WAN and analytics: A marriage made for the new normal (Network World)
How to protect algorithms as intellectual property (CSO)
Your exposure to analytics may come through IT data, such as developing metrics and insights from agile, devops, or website metrics. There’s no better way to learn the basic skills and tools around data, analytics, and machine learning than to apply them to data that you know and that you can mine for insights to drive actions.
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