Loading...
You are here:  Home  >  Data Education  >  Big Data News, Articles, & Education  >  Big Data News  >  Current Article

Qubole Rolls Out Industry’s First Autonomous Data Platform

By   /  September 13, 2017  /  No Comments

by Angela Guess

According to a new press release, “Qubole, the big data-as-a-service company, today announced the immediate availability of three new products – the Qubole Data Service (QDS) Enterprise Edition, QDS Business Edition and Qubole Cloud Agents – components of the first autonomous data platform designed to address the difficulty enterprises face in scaling their data teams and initiatives. Customers are already saving more than $10 million in total cloud compute costs every month with Qubole’s autonomous data platform. ‘Even though big data technologies have greatly advanced, most organizations have trouble operationalizing their big data efforts because data teams simply cannot scale to meet demands for data across the organization,’ said Ashish Thusoo, co-founder and CEO of Qubole. ‘What’s needed is to remove the manual effort that comes with maintaining a big data infrastructure so that data teams are empowered to focus on high-value, strategic work. The automation we’ve built into the Qubole platform delivers true self-service while minimizing costs, optimizing performance and reliability’.”

The release goes on, “Qubole Data Service provides a single platform for ETL, reporting, ad-hoc analysis, stream processing and machine learning, helping data teams at companies such as Lyft, Pinterest and Under Armour be more productive and reduce the costs of their data initiatives. QDS runs on AWS, Microsoft Azure and Oracle Bare Metal Cloud, taking full advantage of the elasticity and scale of the cloud. It also supports the leading open-source engines, including Apache Spark, Hadoop, Presto, Hive and others – all optimized for the cloud. The next-generation QDS platform, first revealed at Data Platforms 2017 in May, self-manages and self-optimizes, allowing data teams to focus on business outcomes rather than managing the platform. The new architecture analyzes metadata (queries, clusters, users, data, etc.) generated by platform usage and applies machine learning and artificial intelligence to create alerts, insights, and recommendations, and offers autonomous agents that perform actions automatically.”

Read more at qubole.com.

Photo credit: Qubole

You might also like...

Data Science Use Cases

Read More →