Cloud Looms Large for Big Data in 2020

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Big Data in 2020

Big Data in 2020- If you’re involved with big data in 2020, then it will be hard to avoid the cloud, which has become the de-facto standard platform for storing and processing vast amounts of data. The cloud will change quickly this year, as cloud giants battle for supremacy. Successfully navigating these dynamics in the cloud could mean the difference between celebrating a big data victory and cleaning up a digital mess.

The modern cloud stack relies on Kubernetes for container orchestration. Expect progress to be made in getting big data and AI workloads enabled on Kubernetes this year, or what Haoyuan “HY” Li, founder and CTO of Alluxio, calls “Kubernetifying” the analytics stack.

“While containers and Kubernetes works exceptionally well for stateless applications like Web servers and self-contained databases, we haven’t seen a ton of container usage when it comes to advanced analytics and AI,” Li says. “In 2020, we’ll see a shift to AI and analytic workloads becoming more mainstream in Kubernetes land. ‘Kubernetifying’ the analytics stack will mean solving for data sharing and elasticity by moving data from remote data silos into K8s clusters for tighter data locality.”

At this point, we have reached a critical mass of cloud-native analytics apps, and the cloud will resign supreme in 2020 because of it, say two Information Builders vice presidents, Eric Raab and Kabir Choudry.

“Organizations using BI and analytics tools fall into one of three groups today: those currently operating in the cloud, those migrating to the cloud, and those discussing a migration to the cloud,” Raab and Choudry say. “While they may have been held back in the past by concerns over whether their platform’s architecture is designed to integrate with and exploit a cloud ecosystem, there are now proven solutions that are purpose-built for cloud-based operation. 2020 will see the floodgates open with organizations moving to the cloud to take advantage of the usability, scalability and flexibility of cloud-native solutions.”

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Article Credit: Datanami