Mastering Data Discovery on Cloud Data Lakes

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Presented by

Rangasayee Chandrasekaran, Product Manager, Qubole

About this talk

In order to capture and analyze new and different types of data, corporations are augmenting their data warehouses and data marts with cloud data lakes. Certainly, capturing new and different types of data is important, but providing access to all users, providing tools that allow them to work the way they already do, and deriving value from those datasets remains the ultimate goal. In this webinar, we will outline data processing challenges faced by analysts in the enterprise and a live demo of Qubole's Workbench—a powerful user interface that reduces time-to-insight by extending Qubole's multi-engine capabilities to data analysts and data scientists. Workbench enables data discovery combining unstructured, semi-structured, and structured data in data lakes or data warehouses for analytics, machine learning, or processing with engines such as Apache Spark. Attendees will learn: -- Common data processing challenges for analytics -- The value of data lakes -- Best practices for working with structured and semi-structured datasets -- When to use Apache Spark, Presto and other engines

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Tune in to hear from open data lake platform leaders and engineers discuss everything from continuous date engineering on data lakes for machine learning, streaming analytics, ad-hoc analytics and data exploration in the cloud. The interactive talks are designed for both data engineers, data analysts and data scientists that want to learn about some of the challenges and solutions for use cases seen in data-driven organizations. Learn more about Qubole: http://bit.ly/AboutQubole