Qubole Unveils Cloud-Native Solution Leveraging Amazon SageMaker to Advance Machine Learning
SANTA CLARA, Calif., Nov. 27, 2018 (GLOBE NEWSWIRE) -- Qubole, the data activation company, today announced a solution that runs on Amazon SageMaker, making it one of the first cloud-native data platform companies with a solution of this kind. The new solution allows data scientists to harness the power of Machine Learning (ML), using Qubole Notebooks and Apache Spark to explore, cleanse, and prepare data, while leveraging the power of Amazon Web Services (AWS) to build, train, and deploy ML models at any scale.
“Machine learning is quickly gaining traction with developers, and we are exploring new ways to eliminate the obstacles traditionally associated with building and deploying machine learning models,” said Ken Chestnut, senior manager, Partner Ecosystem, Amazon Web Services, Inc. “We’re delighted to work with Qubole to help developers and data scientists remove the heavy lifting typically associated with the model development process.”
Processing and preparing large amounts of data from multiple sources is the biggest challenge that data scientists face. This solution is uniquely suited to help data scientists manage their data in a way that is both comprehensive and seamless. Amazon SageMaker provides one of the largest libraries of algorithms, while Qubole expedites the data prep and deployment.
“Qubole and Amazon SageMaker give us an efficient solution for end-to-end data preparation and data science. My team can easily prep data and define a model in Qubole, then automatically push it to Amazon SageMaker to train the model and make it available immediately,” said Peyton McCullough, senior data scientist & machine learning engineer at Ibotta. “We can now train and deploy new ML products within days using much greater volumes of data than before.”
“The availability of data and compute capacity on the cloud is fueling tremendous advancements, allowing our customers to use machine learning to identify new revenue opportunities, drive process efficiencies, or curtail risks,” said Ashish Thusoo, Co-Founder and CEO, Qubole. “By introducing a solution for Amazon SageMaker, Qubole is further enhancing its offering to provide a way for businesses to utilize the full power of machine learning while simultaneously driving down costs and optimizing results.”
Qubole has created numerous innovations that adopt open source technologies including Spark, Hadoop, Presto, and Hive to take full advantage of cloud architectures and optimize the compute resources for processing data. By utilizing compute resources more efficiently, customers pay only for what they use and avoid overpaying or over-provisioning, which is commonplace today. The solution is available now. You can find more information on the Qubole and Amazon SageMaker solution on www.qubole.com.
Connect with Qubole at AWS re:Invent 2018Qubole will be at AWS re:Invent from Nov. 26-30 at The Venetian Sands Las Vegas in booth #1703. To request a meeting with Qubole executives at the Aria Hotel, please click on this link.
About QuboleQubole is revolutionizing the way companies activate their data--the process of putting data into active use across their organizations. With Qubole’s cloud-native Data Platform for analytics and machine learning, companies exponentially activate petabytes of data faster, for everyone and any use case, while continuously lowering costs. Qubole overcomes the challenges of expanding users, use cases, and variety and volume of data while constrained by limited budgets and a global shortage of big data skills. Qubole’s intelligent automation and self-service supercharge productivity, while workload-aware auto-scaling and real-time spot buying drive down compute costs dramatically. Qubole offers a platform that delivers freedom of choice, eliminating legacy lock in--use any engine, any tool, and any cloud to match your company’s needs. Qubole investors include CRV, Harmony Partners, IVP, Lightspeed Venture Partners, Norwest Venture Partners, and Singtel Innov8. For more information visit us online.
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