AWS Best Practices for DDoS Resiliency

whitePaper | September 8, 2022

Enterprises today have to contend with exponentially increasing volumes of batch and streaming data, comprising a variety of structured, unstructured, and semi structured data types, and originating from an expanding number of disparate sources located on-premises, in the cloud and at the edge.

whitePaper | August 12, 2021

This BARC Score report will evaluate BI & analytics platforms on a range of features, from data visualization capabilities to semantic modeling abilities, performance and speed to automation capabilities.

whitePaper | August 25, 2022

The new PowerMax 2500 and 8500 storage systems with PowerMaxOS 10 feature some of the most advanced performance, data protection, data reduction, and data mobility servicing enterprise workloads and applications. The new PowerMax systems come with large DRAM for user data and persistent memory for metadata, end-to-end NVMe, 100 Gbit RDMA fabric, real-time machine learning, 64-bit native file services, seamless cloud mobility, and ability to deliver millions of IOPS at submillisecond latency.

whitePaper | August 9, 2022

Data virtualization helps organizations access data across disparate sources and deliver a unified view of the data faster, cheaper, and using fewer resources than traditional data integration approaches. In this TEI, data virtualization delivered 83% reduction in time-torevenue and 65% decrease in delivery times over extract, transform, and load (ETL) processes.

whitePaper | February 26, 2020

El cambio de paradigma que se está extendiendo por el ámbito tecnológico y empresarial es cada día más evidente. La transición a cloud computing está llegando a su punto de inflexión. Las fusiones y adquisiciones han proliferado. Además, con un número cada vez mayor de usuarios finales que operan fuera del entorno empresarial, los departamentos de TI deben prestar servicio a un ecosistema de usuarios cada vez más diverso, distribuido y exigente

whitePaper | June 27, 2023

Data mesh is an innovative approach to data management that offers a solution to the most common challenges organizations face when dealing with large-scale data management. Data mesh concept consists of four key principles for large-scale data management in a multi-tiered, multi-domain organizational structure: domainoriented ownership, data as product, federated computational governance and a self-service data platform. These all promote a more agile, efficient and scalable data architecture. However, one of the central challenges to implementing data mesh is designing decentralized governance mechanisms that align with its core principles.