How big data engines are used for exploring and preparing data, building pipelines, and delivering data sets to ML applications
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Rapidly deploy analytics and machine learning with Apache Spark, Hadoop, and Presto with Qubole on the Google Cloud Platform.
Learn more about Workload-Aware-Auto-Scaling-- an alternative architectural approach to Auto-Scaling that is better suited for the Cloud and applications like Hadoop, Spark and Presto.
How to make all of your data available to users for a multitude of use cases, ranging from analytics to machine learning and artificial intelligence.
Key criteria to consider when evaluating cloud data platforms
Security strategies to protect your information and how our security model works with AWS
Security strategies to protect your data on Microsoft Azure
Tips on how to choose the best SQL Engine for your use case and data workloads
TDWI drills into the data, tools, and platform requirements for machine learning
How Qubole can help with GDPR compliance