A Benchmarking Case Study of Virtualized Hadoop Performance on VMware vSphere 5

whitePaper | July 12, 2022

In many ways, 2022 has been an exercise in dealing with the reeling of the Covid-19 pandemic. All over the world, supply chain issues have led to a myriad of challenges for enterprises, leading to deep shifts in how we do business and unraveling many of our assumptions about how society operates.

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 | March 12, 2020

This point of view is an exploration of the possibilities engendered by rethinking the role of data scientists in the wake of industrial revolution. It might be claimed that current trends in industrial revolution reflect a paradigm shift towards data centric processing with data science playing an increasingly critical role. This point of view also explicitly highlights the potential role of Data scientists as an emerging phenomenon, and then to show some of the benefits that this role can bring as we move towards industrial disruption

whitePaper | September 26, 2022

Communications service provider (SP) traffic volumes are progressively increasing as networks evolve, user devices gain greater capacity, and applications engaging with advanced network data such as that from the 5G standalone (5G SA) network exposure function (NEF) start to deliver on customer expectations. Cloudification of network functions — virtualized network functions (VNFs) and cloud-native network functions (CNFs) — is placing new burdens on old systems and processes not designed to manage intent-based network architecture. Silos of data locked within many installed systems keep transformation efforts from reaching anticipated objectives.

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.

whitePaper | December 23, 2022

From volatile markets and tough competition to the increasingly stringent demands of government regulators and customers alike, there’s no shortage of challenges ahead for the mining industry. To navigate these obstacles and others all while improving profitability, mining companies are seeking innovative ways to optimize the reliability, efficiency, and safety of their operations. Many industry leaders are already finding the answers they are looking for in their operations data.