As businesses increasingly migrate workloads to the cloud, many encounter a recurring challenge: balancing the need for cost efficiency with the demand for high performance. The cloud offers unparalleled scalability and agility, but hidden expenses and performance bottlenecks often hinder organizations from fully reaping its benefits. Striking the right balance is no easy feat—but it’s far from impossible.
Artificial intelligence isn’t just transforming how we build and operate—it’s also redefining how we store, manage, and move data.
Effective copy data management (CDM) is critical for ensuring organizational data integrity, security, and compliance. With growing data complexities and diverse use cases, establishing a well-structured governance framework is more important than ever. This checklist provides a comprehensive guide to building a strong CDM governance practice, from defining roles and responsibilities to identifying compliance standards and risk mitigation strategies. Let’s dive into the 8 essential steps to streamline your CDM approach and optimize data use while minimizing risks:
Franciscan Health, a 12-hospital system serving communities from Indianapolis to Chicago, is leveraging cutting-edge technology to enhance its operations and patient care. Known for its commitment to innovation, Franciscan has embraced telemedicine, virtual care, and advanced analytics to better serve patients wherever they are. Central to this transformation is its strategic partnership with Silk, whose software-defined cloud storage platform has enabled Franciscan to optimize its data infrastructure.
As your business grows and your data needs expand, more and more teams become consumers of your data. What was once the domain of ITOps has expanded to CloudOps, data teams, generative AI tools and agents, and various lines of business needing to consume and process data. While you may have teams or individuals charged with data governance and data-quality management, the subset of that responsibility, copy data management (CDM), is often an afterthought.
As enterprises increasingly adopt AI-driven analytics, the demand for efficient data access continues to rise. Oracle Autonomous Data Warehouse (ADW) is a powerful platform for analytical workloads, but AI-enhanced processes—such as Agentic AI, Retrieval-Augmented Generation (RAG), and predictive modelling—place new strains on data management strategies.
The healthcare industry is experiencing a pivotal transformation. Cloud technology has moved beyond a trend to become a cornerstone for innovation, cost savings, and operational efficiency. Yet, for many healthcare organizations, the journey to the cloud is as daunting as it is promising. In this blog, we explore the trends driving cloud adoption in healthcare, the benefits it delivers, and the strategies to unlock its full potential.
I was fortunate to be part of a strong Silk contingent in Vegas at “Google Cloud Next 2025”. Being there, I had the opportunity to witness first-hand the impressive rate of change in IT being driven be the rapid adoption of AI across the industry. Silk was proud to see both our products and our customers featuring in a variety of sessions. Two of our joint customers Wayfair and JB Hunt were both highlighted for the innovation they are delivering with AI. The conference was very well attended, every seat in the Michlob Ultra Arena was taken for the keynote and the Allegiant Stadium was packed for the Next at Night concert. The energy and enthusiasm of so many attendees was truly infectious.
The cloud offers organizations the agility and scalability they need to innovate quickly. But when it comes to cost efficiency, many businesses find themselves spending far more than expected. Two of the biggest culprits? Overpaying for low latency and overprovisioning cloud resources. These issues not only inflate costs but also leave organizations struggling to balance performance and efficiency.
In today’s digital landscape, enterprises rely on databases to power critical applications, analytics, and AI-driven insights. However, as organizations scale, so do the challenges of managing database operations efficiently. Traditional database management approaches often lead to performance bottlenecks, increasing costs, and complex operational workflows. This is where Silk Echo transforms the game, providing a high-performance, cost-efficient solution for streamlining database operations.