Billed as a cloud-native data platform for analytics, AI, and machine learning, Qubole offers solutions for customer engagement, digital transformation, data-driven products, digital marketing, modernization, and security intelligence. It claims fast time to value, multi-cloud support, 10x administrator productivity, a 1:200 operator-to-user ratio, and lower cloud costs. To read this article in full, please click… Continue reading Qubole review: Self-service big data analytics
How can you build a data-driven culture and spur digital transformation without thinking through who should be responsible for your data? Let’s do that together. Data engineers and data scientists each occupy critical roles. Data engineers manage the data infrastructure and are in charge of designing, building, and integrating data workflows, pipelines, and the ETL… Continue reading IDG Contributor Network: Who should be responsible for your data? The knowledge scientist
Applications are permeating the online economy. However, it’s not entirely clear whether their deployment is moving in a mainly centripetal or centrifugal direction—that is, whether they are gravitating to the cloud center or moving outward to the edge. To read this article in full, please click here (Insider Story) from InfoWorld Big Data https://ift.tt/2JgrNKc via… Continue reading Will data gravity favor the cloud or the edge?
There’s data, and then there’s big data. So, what’s the difference? Big data defined A clear big data definition can be difficult to pin down because big data can cover a multitude of use cases. But in general the term refers to sets of data that are so large in volume and so complex that… Continue reading What is big data analytics? Fast answers from diverse data sets
In his 2017 Amazon shareholder letter, Jeff Bezos wrote something interesting about Alexa, Amazon’s voice-driven intelligent assistant: In the U.S., U.K., and Germany, we’ve improved Alexa’s spoken language understanding by more than 25% over the last 12 months through enhancements in Alexa’s machine learning components and the use of semi-supervised learning techniques. (These semi-supervised learning… Continue reading Semi-supervised learning explained
Traditional relational databases have been highly effective at handling large sets of structured data. That’s because structured data conforms nicely to a fixed schema model of neat columns and rows that can be manipulated using SQL commands to establish relationships and obtain results. Then big data came along. To read this article in full, please… Continue reading How Qubole addresses Apache Spark challenges
Not every regression or classification problem needs to be solved with deep learning. For that matter, not every regression or classification problem needs to be solved with machine learning. After all, many data sets can be modeled analytically or with simple statistical procedures. To read this article in full, please click here (Insider Story) from… Continue reading Deep learning frameworks: PyTorch vs. TensorFlow