Governance of Big Data development ecosystems

whitePaper | October 27, 2022

Data governance is on everyone’s mind as we move from a static model of data to a dynamic, living, breathing data architecture. As many brilliant people have already said, data — and knowledge in general — is full of “ghosts,” or implicit knowledge existing within any organization that never makes it to documentation. Ghosts affect companies in both data and people spheres, making it challenging to modernize legacy architectures or bring new talent on board. Even more, it makes using data a challenge.

whitePaper | October 10, 2022

Companies undergoing digital transformation must make data available to all stakeholders. However, outdated security and governance tools can prevent companies from freeing their data without opening themselves up to new risks.

whitePaper | June 2, 2022

Data lakeshold enormous promise in supporting modern enterprise data architectures. Their ability to store a full variety of data types and handle ever-larger data volumes generated at high velocity have contributed to their widespread adoption.

whitePaper | August 20, 2021

While finding and creating insights can often feel like luck, there are proven methodologies you can use to ensure you’re seeing regular insight from your on-hand data. Access this short e-book to learn how you can start seeing regular, valuable insight success from you big data and analytics investments.

whitePaper | December 30, 2022

This white paper details Dell CloudIQ, the cloud-based AIOps proactive monitoring and predictive analytics application for Dell systems. It describes how it uses machine learning and other algorithms, notifications, and recommendations to help you optimize compute, storage, hypercoverged infrastructure, data protection, and network health, performance, and capacity.

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