Sisense Debuts Cloud-Native Architecture, Launches AI Exploration with Q3 2019 Product Updates

Features New AI-Driven Augmented Analytics, Enterprise-Grade Cloud-Native Architecture, Devops Tools and 40+ Certified Data Connectors

Sisense, the world’s leading modern platform for analytics builders, unveiled its Q3 2019 product updates, including AI-driven innovations designed to empower users to answer questions they didn’t know they had, a multi-cloud architecture to deploy analytics at scale, and critical features to empower data engineers, product developers, business analysts, and business users.

Read More: Salesforce Completes Acquisition of Tableau

As previewed at Sisense Eureka!, Sisense is debuting Cloud-Native Sisense, the newly rearchitected and purpose-built cloud-native architecture of Sisense’s analytics platform. Offered alongside Sisense’s existing Windows-based option, the unique cloud-native architecture is built for multi-cloud support by utilizing a modern containerized microservices architecture that leverages best-of-breed open-source technologies, including Linux, Kubernetes and Docker Orchestration. Cloud-Native Sisense also offers the first integrations with Periscope Data, which merged with Sisense in May.

Read More: Top Deep Learning Frameworks of 2019 and How Do They Compare

The release also launches AI Exploration, a new augmented analytics capability that automatically generates visualizations and deeper insights from known KPIs by leveraging machine learning to explore underlying data and behavior of all users. With Sisense AI Exploration, end-users are guided toward the answers of questions they didn’t know they had, while dashboard builders can instantly reveal the most important data insights to drive their business forward.

“Every analytics builder stands to gain from the significant improvements available in Sisense,” said Harry Glaser, CMO at Sisense. “Today’s release empowers business users to explore and answer questions they didn’t even know they had, while also enhancing the experience for data engineers and developers who need to more rapidly build, embed and deploy analytic apps.”

Read More: AI Cameras are Clicking Magical Pictures and Videos