Moving on-premises legacy data and analytics workloads to the cloud is unavoidable if you want to overcome infrastructural constraints, facilitate proactive analytics, and lower costs.
You need a service that enables seamless scalability for petabyte-scale data processing, interactive analytics, and machine learning. However, end-to-end, automated workload transformation and optimization on serverless services is not straightforward.
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Imagine you’re a luxury brand releasing a product to a rapt and loyal audience. But instead of receiving rave reviews, your product incites controversy—and social chatter swells around that negative impression. Suddenly, the brand is making headlines that threaten its reputation and could alienate customers. How can you implemen
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In this webinar, Heap’s head of Data Science, David Robinson, will talk about why we took a data-science-led approach to insights that starts with the questions teams actually care about. He’ll also talk about how a combined quantitative + qualitative platform gives teams the predictive information they need and the context that makes that information actionable.
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Xoriant Corporation
Are you unsure of how to leverage Big Data and select among the many technologies surrounding it? Don't worry - you aren't alone. Here and watch this video to know how you can address the Big Data challenges using Hadoop.
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