Unlocking the value of data with APIs

whitePaper | September 28, 2022

Your customers need more than dashboards. They need instant, actionable insights and analytics. And you need to offer more than basic analytics to futureproof your application. Learn how embedding AI-powered analytics gives you a sustainable competitive advantage. Download the complete guide today.

whitePaper | June 24, 2022

This new technology guide from DDN shows how optimized storage has a unique opportunity to become much more than a siloed repository for the deluge of data constantly generated in today’s hyper-connected world, but rather a platform that shares and delivers data to create competitive business value. The intended audience for this important new technology guide includes enterprise thought leaders (CIOs, director level IT, etc.), along with data scientists and data engineers who are a seeking guidance in terms of infrastructure for AI and DL in terms of specialized hardware. The emphasis of the guide is “real world” applications, workloads, and present day challenges.

whitePaper | September 2, 2022

The past several years brought about an abundance of change in how we as individuals, organizations, and a society approach daily life. Our views on ethics are evolving and our sense of acting with purpose is increasing – and as part of that, diversity, equity, and inclusion have become top corporate and personal objectives. Consumers are asking the brands they engage with for more transparency and are tasking them to act in ways that are fair and respectful to all stakeholders: suppliers, employees, prospects, and anyone else who interacts with the brand.

whitePaper | August 23, 2022

Today, there is a real-time, global, tectonic shift in the workplace caused by digital transformation. Accelerated by the Covid pandemic, this digital transformation has created never-seen-before opportunities and significant workplace disruption. Fully realizing the new market opportunities demands a modernized workforce.

whitePaper | December 23, 2019

We are witnessing a new genre of companies shaping the business landscape by leveraging emerging technologies and applying them with such potency to create competitive advantage. These organisations have a quest to scale; they are big on customer experience; they are open to partnerships and are able to deploy their products and services at scale through APIs; they are big adopters of the cloud and quite often are born in the cloud; they embrace design thinking and are happy to return to first principles to find innovative solutions to business problems; and they are relentless at leveraging the power of artificial intelligence (AI) for insights and decision making.

whitePaper | July 10, 2020

There’s no arguing that preventing failures and accidents is critical for industry. Unexpected incidents can grind operations to a halt for extended periods of time and necessitate expensive repairs. Just 12 hours of downtime for an oil production platform could cost six to eight million dollars in lost production opportunity alone. A single day of grounding for a plane costs roughly four to five million dollars. Because of these disruptions, industrial sectors are always on the lookout for newer, better maintenance methods, and the approach on everyone’s lips right now is predictive maintenance. While everyone agrees on the name, there is less consensus on what it means or how to implement it. But to truly unlock the potential of predictive maintenance, it needs to be paired with artificial intelligence (AI) and machine learning (ML).