Enterprise-Scale Big Data Analytics on Google Cloud Platform

July 16, 2020

As companies scale their data infrastructure on Google Cloud, they need a self-service data platform with integrated tools that enables easier, more collaborative processing of big data workloads. Join Qubole and Google experts to learn: - Why a unified experience with native notebooks, a command workbench, and integrated Apache Airflow are a must for enabling data engineers and data scientists to collaborate using the tools, languages, and engines they are familiar with. - The importance of enhanced versions of Apache Spark, Hadoop, Hive and Airflow, along with dedicated support and specialized engineering teams by engine, for your big data analytics projects. - How workload-aware autoscaling, aggressive downscaling, intelligent Preemptible VM support, and other administration capabilities are critical for proper scalability and reduced TCO. - How you can deliver day-1 self-service access to process the data in your GCP data lake or BigQuery data warehouse, with enterprise-grade security.

Previous Video
Key Differences Between On-Prem and Cloud Data Platforms
Key Differences Between On-Prem and Cloud Data Platforms

Cloud service models have become the new norm for enterprise deployments in almost every category — and big...

Next Video
Qubole On-Demand: Discover our Open Data Lake Platform
Qubole On-Demand: Discover our Open Data Lake Platform

Watch this on-demand demo to learn how the most data-driven organizations are able to significantly enhance...