Semantics and virtualization, data integration and data governance on the way to the cloud
It’s official – data analytics is swiftly moving to the cloud. AtScale is facilitating this, and CEO Chris Lynch shares his insights the hows and whys, in light of the unveiling of AtScale’s Adaptive Analytics 2020.1
AtScale is a data virtualization provider for analytics. What this means is that AtScale provides an abstraction layer that enables its users to access the underlying data stores it supports in a streamlined way. Last time we covered AtScale, in November 2016, AtScale had just broken out of the Hadoop box. Today, AtScale announced what it dubs a leap in multi-cloud and hybrid cloud analytics, data platform flexibility and time-to-analysis with the launch of its Adaptive Analytics 2020.1 platform release.
ZDNet connected with AtScale CEO Chris Lynch to discuss the data and analytics market and AtScale’s positioning in it.
The announcement of AtScale Adaptive Analytics 2020.1 emphasizes secure, self-service analysis while speeding up performance of underlying data stores. According to AtScale’s Cloud Data Warehouse Benchmark Report, AtScale reduces compute costs by 10x, improves query performance by 12.5x and enhances user concurrency by 61x.
The way AtScale achieves those results is still the same, conceptually, it has been doing this since 2016: design, cache, query. Additional enhancements in AtScale 2020.1 include a virtual cube catalog for simplified management of data assets and granular policy control that integrates natively with existing enterprise data catalog offerings.