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Discover the platform's data engineering feature to efficiently manage data pipelines with the flexibility of preferred programming language and data processing frameworks. Learn to create clusters the right way to manage the cloud spend and meet the SLAs.
See how to handle large datasets of ad-hoc queries from multiple end-users without operational complexity. Learn more about improving workloads performance by implementing a data layout strategy, such as columnar data formats, statics collections. Power ad-hoc or batch queries on large datasets with cloud-optimized open-source frameworks Presto, Hive, SparkSQL.
Watch a demo on the platform's Machine Learning capabilities and learn how to leverage Jupyter or Qubole notebooks to monitor application status and job progress, and use the integrated package manager to update the libraries at scale. Understand how to build an ML model against the dataset to do market basket analysis.
Free access to Qubole for 30 days to build data pipelines, bring machine learning to production, and analyze any data type from any data source.