Exploring The Key Pillars of a Modern Resilient Data Architecture

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As everyone pushes for real-time analytics, more responsive online services, and more protection against cybercrime, data resiliency has moved front and center. Put simply, data must be available at all times. This requires a shift in con­ventional thinking toward data resiliency strategies in rec­ognition of the fact that it is no longer a technical issue; it’s a business issue.

“A resilient data architecture is about getting the right data into the right decision-making pro­cesses at the right time,” said Amy O’Connor, chief data and information officer for Precisely. “To match the increasing velocity and scope of today’s decision-making processes, data architectures must be highly available, must scale on demand, and must support automated decision making like machine learning and AI.”

The challenge for a long time has been that data resiliency has been a backwater IT concern, not seen with urgency at a business level—an attitude that has been changing in recent years, especially as the disruption created by the pandemic set in. “The last 2 years have been a wake-up call for orga­nizations to shore up their data operations,” said Sudhir Mehta, global vice president of transformation solutions at Lexmark International. “Companies are now looking at data architectures that can readily adapt to all types of risks, beyond the narrow focus of a natural disaster or network disruption. The impact of ongoing remote work, supply chain disruptions, and an increasing number of cyberat­tacks all contribute to expanding the paradigm of data resil­iency. At the same time, resilience empowers organizations to discover new ways to innovate, drive value, and catalyze data to deliver business results.”

This confluence of crises has made data resiliency a top-level business priority. “Typically, resilience has been treated as a bolt-on to the database,” said Karthik Ranganathan, founder and CTO of Yugabyte. “But this causes a lot of pain down the road. It is also operationally expensive and difficult to execute. That makes it important to take the necessary time to design the right level of resilience into a data architecture.”


COVID-19, competition, and cybercrime are creating greater awareness of the need for data resil­iency. “Competition is a key driver of resilient data architecture,” said Sharad Varshney, CEO of OvalEdge. “Organizations must be able to com­pute and access analytics faster than their competitors. A resilient data architecture provides the agility and scalability required to ensure busi­nesses stay ahead of the curve. They can avoid the high costs of manual scaling, reporting bottlenecks, and issues with dispersed data.”

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