Gain faster and easier access to trusted data without data engineering.
Adapt to changing workloads quickly whichever cloud platform the data resides on.
Facilitate consistent joins between tables and apply ML to build acceleration structures that can reduce data query times from 2X to 1000X depending on the datasets involved.
Today businesses require real-time data. AtScale creates virtualized connections to disparate data stores to make them centrally available for discovery and querying.
AtScale provides data analysts with access to data from multiple sources for advanced analytics.
AtScale gives enterprises the ability to unify fragmented data avoiding the risks of incomplete or inaccurate data analysis.
AtScale's business logic governs how data is joined to enable consistency and reliability across business intelligence tools.
AtScale A3 offers intelligent data virtualization and autonomous data engineering to visually create a network of databases, relate the data across data platforms to delivery a centralized, data repository for analysts.
Reduce complexity using AtScale’s Universal Semantic Layer requiring no data movement, minimizing the latency between IT and BI when preparing data for consumption, and reducing preparation time from weeks to minutes.
Leverage AtScale’s pursuit of ‘Zero Trust’. Its numerous patents on security features ranging from MFA to native platform security support and True Delegation.
As data proliferates, companies are falling behind in their ability to manage and leverage that data for competitive advantage. Companies with effective data analytics are 18X more likely to make better, faster decisions for a competitive edge. AtScale Adaptive Analytics makes cross-platform data available to analysts quickly and easily.
Ensure that data across the organization is available for comprehensive analysis.
Apply autonomous systems to increase data reliability, speed, and security while reducing delays from manual data engineering.
Automate and govern access privileges to data while respecting global and local security configurations.
Simplify the process of bringing data together and providing high-speed insights in a complex, hybrid cloud environment.
Toyota had thousands of data analysts on their IoT and Finance teams using Tableau and Power BI. As part of the move to a data lake on Hadoop, they wanted to provide a single set of business definitions across this user constituency.
Toyota’s data modelers used AtScale’s Adaptive Analytics Fabric to craft virtual cubes that could be easily accessed by analysts in Tableau and Power BI, and that could scale as data grew without the need for complex manual cube rebuilds.
Fortune 50 DIY retailer optimizes a cloud data platform to increase ROI per analysis.
LEARN MOREToyota leverages AtScale, accelerating time-to-insight from weeks to minutes.
LEARN MOREFortune 100 industrial conglomerate embraces the cloud without business disruption.
VIEW CUSTOMERSLearn the 6 principles of modern data architecture including viewing data as a shared asset and creating a common vocabulary.
READ NOWFour practical ways intelligent data virtualization can improve the cloud migration and data architecture modernization journey.
DOWNLOAD NOWLearn how the evolution of the data fabric concept and the use of ‘autonomic’ approaches let modern systems employ AI/ML driven automation to adapt based on user behaviors.
READ NOWDeliver data for business intelligence and machine learning analytics just-in-time.
Shift resources from managing distributed data silos—to analyzing them.
