Introducing Apache Druid

whitePaper | May 5, 2021

Over the last decade, interest in the field of data science has not only increased enormously, but has also changed and developed considerably. In view of the new technological advances and the constant growth of data, we expect Data Science to continue to develop strongly in 2021. We have identified 7 trends that will be relevant for the coming year.

whitePaper | November 26, 2019

There has been much said about the Internet of Things (IoT) and what it can bring to business and society - creating a more deeply connected world, informed by data sourced from connected things, made better by smarter, more meaningful actions and interactions. These views often focus on how IoT technical solutions can deliver this new future, emphasizing the technology DNA of IoT devices, networks and applications. We have found, however, both through research and experience, that while technology is, in fact, the core of IoT’s DNA; it is just a piece of the puzzle needed to deliver on IoT’s promise. With 60% of IoT projects still struggling to move out of proof-of-concept and scale successfully2 there is more to IoT success than technology alone. What is needed and how can business leaders plan better for IoT success?

whitePaper | June 29, 2022

For (oh so many) years, we’ve been hearing about the “promise” of big data. Much of the buzz focused on getting people prepared for the onslaught of bigger data sets – and what IT needed to do to help the business make sense of this information.

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 | December 9, 2022

In Data Governance Methodology, we described why a modern active data governance methodology is superior to a traditional top-down methodology and how active data governance is supported by continuous improvement. We also discussed how a data governance process based on continuous improvement is a key component of a DataOps process.

whitePaper | October 17, 2022

Today, massive amounts of data are collected, processed, and stored for a range of analytical purposes around the world. Every customer, device, transaction, email, and image leaves a data trail. At present, this data is growing too big, changing too fast, and becoming hyper distributed. The traditional ways of doing integration and analytics are no longer viable or scalable. It is not feasible to create millions of data pipelines and to continue moving large amounts of raw data to a data lake or a centralized data warehouse.