What people are saying about us.
What people are saying about us.
Emerging cloud security risks are causing fear among executives. What is at stake? Matthew Baird, Co-founder and CTO of AtScale shares insights.
If you’re trying to do business intelligence (BI) on big data and the capability to handle large number of concurrent queries is a key issue for you, Google BigQuery may well be the way to go, according to a new Business Intelligence Benchmark released Thursday by AtScale, a startup specializing in helping organizations enable BI on big data. AtScale’s benchmark found concurrency to be BigQuery’s greatest strength - with a nice user experience to boot.
Cloudera merged with fellow big data management vendor Hortonworks in January 2019 and partnered with IBM in June 2019. AtScale's Chief Strategy Officer Dave Mariani weighs in on this evolution and what it means for a potential AWS face-off.
Chris Lynch, AtScale's CEO, spoke with Dave Vellante and Paul Gillin, co-hosts of theCUBE, SiliconANGLE Media’s mobile livestreaming studio, during the MIT CDOIQ Symposium in Cambridge, Massachusetts. They discussed AtScale’s promise of providing single API access for data analysis, eliminating the business intelligence bottleneck.
AtScale’s Data Warehouse Virtualization Platform and intelia Partner to Accelerate Cloud Data Transformation for Global Enterprises in Australia.
AtScale Co-founder and CTO Matt Baird weighs in on Google's latest round of updates to BigQuery.
As new, data-intensive systems are spun up to keep pace with business needs, maintaining security and data governance is becoming a top concern. AtScale's Chief Strategy Officer and Co-founder Dave Mariani, explains how intelligent data virtualization, a suite of technologies used to provide cloud data transformation of siloed data, is also an ideal solution for orchestrating security policies across the hybrid cloud.
In its bid to make data more easily accessible even across multiple databases and clouds, data virtualization vendor AtScale recently added time-series analysis capabilities. It’s part of the industry trend toward creating “fit for purpose” processing and analysis of Big Data rather than a one-size-fits-all approach. AtScale's Co-Founder and CTO Matt Baird shares insights on the important shift from performance to agility.
At the beginning of July, Microsoft and Oracle announced that they were creating a cloud interoperability partnership. It’s not the only cloud partnership that has been announced in recent weeks and months. Taken together, At the beginning of July, Microsoft and Oracle announced that they were creating a cloud interoperability partnership they all add up to fundamental changes in the cloud space and, ultimately, the way organizations work. We will be taking a deeper dive into the cloud space soon, but with Microsoft and Oracle now together at least in this respect, understanding this partnership is a good indication of future moves and trends.
July 17, 2019: AtScale, the data warehouse virtualization company, today announced its new 2019.2 platform release. The latest release augments AtScale’s autonomous data engineering innovations with the introduction of a sophisticated time-series and time-relative analysis capability for large volumes of data across disparate databases and platforms. This new capability enables data analyst and data science teams to have unencumbered access to large volumes of dispersed operational time-series data. Data consumers can quickly query and configure data for their specific business definitions using the business intelligence (BI), artificial intelligence (AI) or machine learning (ML) tools of their choice.
With the rollout of its 2019.2 platform, AtScale is attempting to make accessing and analyzing big data simpler and faster across both different databases and business intelligence platforms. By improving the machine learning and augmented intelligence capabilities of its platform, AtScale's newest release attempts to speed data querying.
It’s now data, not big data, and the landscape is no longer complete without AI. There's a wave of consolidation in the BI space which raises the question, will there be a new generation of AI? This article does a deep dive into the AI landscape, and includes AtScale as part of the ecosystem.
The proliferation of BI tools presents organizations with a challenge: each business unit may have selected and implemented its own favorite. This is layered on top of the technical barriers involving legacy data silos, security, data governance . The answer is for companies to let end-users choose the BI tool they prefer, and then make it possible for all these tools to connect to the necessary data.
We're proud to see AtScale on the list of the industry's most impactful companies! The insideBIGDATA IMPACT 50 list is made up of companies who have proven their relevance by the way they’re impacting the enterprise through leading edge products and services.
Leapfrogging analytics basics and ignoring automation is a sure route to ruin. This article covers these and other real-life suggestions for success from AtScale's CTO Matt Baird, a Silicon Valley veteran.
A look at how organizations can achieve data independence (being able to do what they want with their data seamlessly), with insights from AtScale's CEO Chris Lynch: “You can’t have big data unless you have all the data."
The consensus seems to be this: Hadoop isn’t dead, and companies should be looking at it, but for what it can do and not to solve all of their problems. Chris Lynch, CEO of AtScale, says the future is all about managing data in a hybrid manner, split between multiple clouds and on-prem.
There’s always the next vendor with a tool for extracting and moving data from one repository to another. Then there’s AtScale, with software that seeks to break the data pipeline mold, replacing it with a way to semantically accelerate the use of active data sources without requiring the typical migration process.
AtScale's CEO Chris Lynch weighs in on the importance of focusing on the data and not getting sidetracked by promises of new AI technology, following the release of a recent study that says the lack of clean, well-managed, and labeled data is a major impediment for enterprises getting value out of AI.
Capitalizing on Market Demand for Data Warehouse Virtualization, Company Appoints Former Storage VP from Citrix to Drive Global Engineering