Students Will Be Able to Conduct Data Analysis on Any Size Data Sets Using the Latest Technologies Such as Apache Spark, Presto, Hive and Hadoop on Qubole’s Self-Service, Infinitely Scalable Cloud Platform
Qubole, the big data as-a-service company, announced today it will be donating time on the Qubole Data Service (QDS) to university classes, giving students and professors easy access to the latest, most powerful data analytics technologies on the most widely used public clouds: Amazon Web Services, Google Cloud and Microsoft Azure.
Qubole will make its platform and QDS product available to ten accredited U.S. universities or university classes via a one-year license, based on eligibility. Qualified universities will also receive complementary training courses and architectural assistance to get started with Qubole.
“Our global economy is increasingly data driven — just about every student entering the workforce in the coming years will need to be well versed in understanding and using data to make decisions and perform their job,” said Qubole CEO, Ashish Thusoo. “Unfortunately, getting access to the latest big data technologies is costly, complicated and something few colleges have the budgets or technical teams to deploy and maintain. Because our platform is cloud based, automated and easy to use, it is not only changing the way businesses use data, but it can also expose more students to the technologies that underpin our data economy, such as Hadoop, Hive, Presto and Apache Spark.”
The Qubole Data Service is a fully managed big data offering that leverages the latest open source technologies, such as Apache Hadoop, Hive, Presto and Spark, to provide the only comprehensive “everything as a service” data analytics platform. With Qubole, data science students can focus on analysis, while ensuring the most efficient use of resources.
Qubole is the data processing engine for organizations across a range of industries, from genetics mapping to real-time marketing to commerce and gaming. The QDS platform was built to be extremely easy to use for any data scientist or analyst, without the need for hardware infrastructure or a team of system admins. For example, QDS automatically sets up and scales up a compute cluster in the cloud to match the needs of the particular job, and then winds down nodes when they’re no longer needed.
To be considered, visit here for more details, eligibility and requirements.