Was Your Information Swimming Naked During The Pandemic?

Similarly, 92% agreed that “Due to drastic changes in customer behavior or other factors during the pandemic, reliable real-time data became even more important for business decisions.”

95% of respondents, for example, agreed that “Making decisions based on accurate, timely analytics and insights has become as important as having accurate transactional data in my organization.”

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Nvidia, Others Hammer Out Tomorrow’s Cloud-Native Supercomputers

Chipmaker Nvidia, for example, is developing data processing units (DPUs) to tackle infrastructure chores for cloud-based supercomputers, which handle some of the most complicated workloads and simulations for medical breakthroughs and understanding the planet.

Jon van Doore, CTO for Climavision, says modeling the data his company works with was traditionally done on Cray supercomputers in the past, usually at datacenters

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Data Lake Best Practices: Prevent Your Data Lake from Turning into a Data Swamp

When appropriately crafted, data lakes can be a centralized source of truth, offering team members valuable flexibility to examine information that impacts business decisions.

A well-maintained data lake has the real potential to transform your business by offering a singular source for your company’s data—in whatever form it may be—that enables your business analysts and data science team to mine information in a scalable, sustainable way.

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The Future Of Healthcare

Since the start of the pandemic, the transformation and digitization of healthcare organizations (HCOs) accelerated at unprecedented rates to usher in consumer centrism, increased accessibility, and enhancements in continuous care.

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Is The Cloud Slower For Analytical Insights?

Reliable real-time data and analytics for decision-making became more critical. But many IT organizations couldn’t deliver; survey respondents said that the information and insights needed by the business often weren’t available.

There were high levels (95%) of agreement with the very rational statement that, “My organization makes decisions on where/how to process data for analytics and AI based upon the best platform attributes (latency, security, resiliency, and performance/ cost).

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Data Fabrics: Six Top Use Cases

In a nutshell, data fabric technology is the glue that binds all an organization’s data systems together into a cohesive and uniform layer, says Sean Knapp, founder and CEO of Ascend.io, which offers an autonomous dataflow service.

A data fabric gives organizations the ability to maintain complex and disparate data systems while giving business users fast, self-service access to the data they need — no matter where it sits or how it’s previously been siloed,” he explains.

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How Hybrid Multi-Cloud Can Mitigate Current Supply Chain Woes

Enabling applications, including the most business-critical ones, to run in public cloud when they were not built to do so requires a costly and time-consuming refactoring process.

Hybrid multi-cloud, or an IT environment providing unified infrastructure operations and management across private and public clouds, is perfectly poised to help bridge the gap businesses face due to supply chain issues.

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As applications drive business, iPaaS comes of age

For iPaaS to become this digital core, and help become the glue between systems, it needs to take on the almost-impossible task of integrating data from all apps, automating the building of app connectors within cloud services, connecting on-premises and cloud-based processes, offering connectivity through APIs, and leaning heavily on AI-fueled process automation.

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