Query ANY data source and break down the barriers to knowledge

Federated Queries are the Future of Analytics

Query ANY data source and break down the barriers to knowledge.

Join us on Thursday June 9th, 11:00 AM CST

Can’t attend but don’t want to miss out? Register and we will send you the recording.

Leveraging big data is no longer a luxury. It’s necessary. If you are struggling with complexity, scalability, speed, cost, and reliability, then it is time to see Qubole in action.

Qubole’s Open Data Lake platform provides a single gateway to analyze and interrogate ALL of your company data, wherever it resides and whatever its format. Qubole customers are enjoying a self-service, performant, secure, and affordable environment to rapidly transform source data into actionable insight.

Join us and see how you can:

  • Get a federated view across your structured and unstructured data sources
  • Consume data no requirement to manipulate or move your data
  • Instantaneously gain to your entire data ecosystem

To attend live, or receive a recording of this session, please register below:


PRESENTED BY:

Brian C FlǕg – Presales Solutions Architect

With decades of analytical expertise, Brian is an accomplished technologist who has achieved success in computational solutions, from supercomputing, to cluster and grid computing, to pre and post cloud computing, research, business intelligence, scientific analytics, and engineering, simulations and animations, data sciences, distributed and parallelism computing.

ABOUT QUBOLE

Qubole’s Platform provides end-to-end data lake services such as cloud infrastructure management, data management, continuous data engineering, analytics, and machine learning with near-zero administration. Qubole is trusted by leading brands such as Expedia, Disney, Oracle, and Adobe to spur innovation and to transform their businesses for the era of big data.

No other platform provides the openness and data workload flexibility of Qubole while radically accelerating data lake adoption, reducing time to value, and lowering cloud data lake costs by 50 percent.