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.