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DevOps for Data Science

Speaker: Buck Woody

Duration: 1 hour

DevOps (Developer Operations) is defined as a development process that emphasizes communication and collaboration between product management, software development, and operations, automating the process of solution integration, testing, deployment and infrastructure changes.

All projects involving on-premises software and hardware benefits from DevOps. But hybrid and cloud-only architectures require it – there are so many variables to even setting up the architecture that a dedicated team or developer is often required. And Advanced Analytics projects involving Data Science have even more requirements that are specific to these tasks.

This session explains the processes, procedures, platform options that you have available, along with explaining the tools you need to use to create an effective DevOps solution for your Advanced Analytics projects.

 

Buck Woody  300