Organizations now run diverse, multidisciplinary big data workloads that span data engineering, analytic database, and data science applications. Many of these workloads operate on the same underlying data, and the workloads themselves can be transient or long running in nature. One of the challenges is keeping the data context consistent across these various workloads.
Sudhanshu Arora, Stefan Salandy, Suraj Acharya, Brandon Freeman, Jason Wang, and Shravan Pabba demonstrate how to successfully manage the shared data experience to ensure a consistent experience across all various workloads. You’ll learn how to successfully run a data analytics pipeline in the cloud and integrate data engineering and data analytic workflows and explore considerations and best practices for data analytics pipelines in the cloud. Along the way, you’ll see how to share metadata across workloads in a big data PaaS.
You’ll use the Cloudera Altus PaaS offering, powered by Cloudera Altus SDX, to run various big data workloads.
Sudhanshu Arora is a software engineer at Cloudera, where he leads the development for data management and governance solutions. Previously, Sudhanshu was with the platform team at Informatica, where he helped design and implement its next-generation metadata repository.
Stefan Salandy is a systems engineer at Cloudera.
Brandon Freeman is a Mid-Atlantic region strategic system engineer at Cloudera, specializing in infrastructure, the cloud, and Hadoop. Previously, Brandon was an infrastructure architect at Explorys, working in operations, architecture, and performance optimization for the Cloudera Hadoop environments, where he was responsible for designing, building, and managing many large Hadoop clusters.
Jason Wang is a software engineer at Cloudera focusing on the cloud.
Shravan (Sean) Pabba is a Principal Systems Engineer at Cloudera. He helps Cloudera customers and prospects adopt, architect and build applications using Cloudera Platform. His current area of focus is Cloudera Altus. Before Cloudera, Sean worked as a Solutions Architect at various companies including GigaSpaces and IBM, where he was involved in architecture, design and development of distributed and mainframe applications.
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