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Making Big Data Agile[article] Big data is defined as web-scale, large quantities of data ranging to several TeraBytes (TB) or PetaBytes (PB). Big data is inherently difficult to manage due to its sheer size and free format, which is best summarized by the three Vs (volume, velocity, and variety). |
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What Makes SaaS, Agile, and DevOps a Powerful Combination?[article] Companies unleash their true potential in today’s ever-changing, constantly evolving world through digital transformation. Implementation of cloud-based Software as a Service (SaaS), when combined with Agile methodology and DevOps, represents a strong value proposition |
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Lessons as a Proxy PO[article] Sometimes a challenge can be turned into an opportunity. When our team learned that the business needed to pull their popular Product Owner to focus on another team, a sense of panic set in. There would be a job search that could and did take months. Who would help the team on their path to creating value in the interim? How would we operate? Over time, what seems to be a negative turn of events was turned upside down. |
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5 Tips to Take Your DevOps Pipeline Beyond the Basics[article] The goal of a DevOps pipeline is to create a continuous workflow that includes the entire application lifecycle. But too often, people focus only on the tools and automating everything, not stopping to think whether their processes could further improve performance and efficiency. Let's look at some common challenges to continuous delivery and then learn five tips for refining your DevOps pipeline and taking it to the next level. |
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A Primer on Continuous Testing[article] Continuous testing shortens feedback loops through automated testing that occurs throughout the development lifecycle—hence "continuous." Testing and QA become the responsibility of everyone working on the software, not just testers. Let's look at some proven practices from organizations that have used continuous testing effectively to realize tangible benefits. |
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