Insight

  • Recent technological shifts, including the widespread adoption of AI and shifts in the cost of licensing for hypervisor technology, are forcing IT decision-makers to reevaluate their preconceptions in hybrid cloud architecture and design. Cost increases in hypervisor technology have emerged across the IT world, leading to the exploration of alternatives. The prioritization of AI has fueled an increased focus on both the importance of private data and the need for greater control of infrastructure, reaffirming the significance of data centers, colocation, and hosted private cloud options for private AI. Enterprise Strategy Group, recently surveyed IT professionals to gain insights into these trends.

    To learn more, download the free infographic, Private AI, Virtualization, and Cloud: Transforming the Future of Infrastructure Modernization.

  • Recent technological shifts, including the widespread adoption of AI and shifts in the cost of licensing for hypervisor technology, are forcing IT decision-makers to reevaluate their preconceptions in hybrid cloud architecture and design. Cost increases in hypervisor technology have emerged across the IT world, leading to the exploration of alternatives. The prioritization of AI has fueled an increased focus on both the importance of private data and the need for greater control of infrastructure, reaffirming the significance of data centers, colocation, and hosted private cloud options for private AI.

    To gain further insight into how these trends are impacting the future of on-premises infrastructure investments, architecture, and design, Enterprise Strategy Group surveyed 380 IT professionals at organizations in North America (U.S. and Canada) involved with or responsible for evaluating, purchasing, managing, and building application infrastructure.

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  • This Complete Survey Results presentation focuses on drivers for application deployment locations, hypervisor preferences and plans, platform approaches to hybrid cloud, infrastructure modernization across on-premises and cloud locations, and private AI preferences and initiatives.

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  • The shift in enterprise data strategy has moved beyond enabling better decision-making, now focusing on powering AI at scale. Oracle Database@AWS represents a pivotal development, enabling organizations to unify structured and unstructured data, enforce governance, and help ensure compliance without compromising on performance or flexibility. By running Oracle Database services on Oracle Cloud Infrastructure (OCI) within AWS data centers, enterprises gain the power of Oracle Database 23ai features such as AI Vector Search, combined with access to AWS-native AI tools like Bedrock for Amazon Nova large language models and SageMaker. This collaboration reduces the friction in deploying AI from proof-of-concept to production by providing architectural compatibility, simplified operations, and a unified governance framework. The result is a new foundation for data platforms that meet the requirements of both business decision-making and AI enablement—secure, at scale, and intelligent.

    To learn more, download the free brief, Oracle Expands Multi-cloud Offering With AWS to Meet Enterprise AI Data Strategy.

  • Pure Storage used its recent Accelerate conference to unveil a bold new vision. Based around the concept of the Enterprise Data Cloud, it’s the latest phase in Pure’s mission to disrupt the enterprise data landscape and tackle long-standing challenges within the storage domain head-on, reducing complexity, achieving scale, and, ultimately, enabling organizations to effectively manage their data, rather than storage, in a truly service-oriented fashion.

    To learn more, download the free brief, The End of the Storage Silo? Pure’s Enterprise Data Cloud Promises a New Era for Data Management.

  • Data is the lifeblood of any modern organization, but the sheer volume of unstructured data at many organizations threatens to overwhelm, pushing up costs, introducing risks, and limiting their ability to innovate at a time when the importance of leveraging digital data has never been stronger. These are challenges that Starfish Storage has spent the last decade addressing, with a comprehensive set of federated data management capabilities that help many of the world’s largest organizations control, optimize, and fully leverage their critical unstructured data assets.

    To learn more, download the free brief, Starfish Storage’s Metadata-driven Approach for Unstructured Data Management Strikes a Chord in the AI Era.

  • Organizations face challenges managing the controls they have in place to prevent data loss, especially when it comes to the volume of alerts. Indeed, resource-strapped cybersecurity teams often lack the time to go through the barrage of alerts generated by DLP tools and platforms or the necessary context to quickly disposition alerts. Recent research by Enterprise Strategy Group examined how IT and cybersecurity professionals are navigating challenges with DLP alert management.

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  • Typically a prerequisite for data loss prevention (DLP) strategies, data classification tools allow organizations to determine data’s sensitivity, label data accurately, and apply proper access controls to a variety of data sets. Recent research by Enterprise Strategy Group investigated how organizations are managing data classification in today’s data-intensive operational environments.

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  • VMware recently announced the general availability of VMware Cloud Foundation (VCF) 9.0. In this release, VMware consolidates and simplifies its management experience across virtual machines and containers, while integrating cost optimization and data sovereignty functionality.

    To learn more, download the free brief, VMware Cloud Foundation 9.0: Consolidating the Private Cloud.

  • As data environments become increasingly distributed across multiple clouds and systems, the challenge of maintaining consistent governance, access control, and compliance grows. Databricks Unity Catalog meets this challenge by providing a unified governance layer purpose-built for the modern data stack. It supports structured, unstructured, and federated data, spanning sources like SAP and beyond, as well as AI assets such as models, ensuring that data and AI assets are governed and fresh for decision-making AI and analytics.

    To learn more, download the free brief, Databricks Unity Catalog Establishes Trust and Control Over Your Data.

  • Data Readiness for Impactful Generative AI