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  • Industries Vary Navigation Routes Through Data Readiness Requirements

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    Stephen Catanzano

    All major industries recognize the value of data readiness for successful AI use—after all, AI is only as effective as the data fed into its models. However, recent research by Enterprise Strategy Group, now part of Omdia, discovered that industries vary in their approaches to data readiness, showing differences in influencing factors, challenges encountered, scaling strategies, and success metrics.

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  • Open Source LLMs for Everyone at Scale: Red Hat Acquires Neural Magic

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    Torsten Volk

    Red Hat’s acquisition of Neural Magic addresses enterprise demand for greater performance and cost efficiency when building, deploying, and managing AI-driven applications, enabling organizations to select and optimize open source large language models (LLMs) according to their individual requirements. By integrating Neural Magic’s expertise in inference performance engineering and model optimization, Red Hat strengthens its AI portfolio, complementing existing capabilities for scalable AI lifecycle orchestration across hybrid cloud environments. This combination has the potential to notably increase Red Hat’s differentiation in the rapidly evolving generative AI landscape.

    To learn more, download the free brief, Open Source LLMs for Everyone at Scale: Red Hat Acquires Neural Magic.

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  • Observability in Action: Enhancing Developer Productivity in Real-world Scenarios

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    Torsten Volk

    The Dynatrace Observability for Developers platform focuses on addressing the key reasons why developers often do not take advantage of observability.

    To learn more, download the free brief, Observability in Action: Enhancing Developer Productivity in Real-world Scenarios.

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  • Data Complexity Inhibits Large Midmarket Organizations Along Their AI Journey

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    Stephen Catanzano

    Although teams across industries are eager to unlock the potential of AI within their businesses and operations, they regularly run into roadblocks in integration complexity, data source utilization, and data quality and trust. Recent research by Enterprise Strategy Group, now part of Omdia, revealed that some of these issues might be correlated to organizational size as they are often more acute for certain groups.

    Already an Enterprise Strategy Group client? Log in to read the full report. If you are not yet a Subscription Client but would like to learn more about accessing this report, please contact us. 

  • The Future of BI With Looker and Gemini

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    Mike Leone

    With rising industry demands for increased user accessibility, advanced analytics capabilities, and improved operational efficiency, Google Cloud has announced significant enhancements to Looker. Deep integrations with Gemini for improved conversational analytics and enhanced reporting is set to empower wider user adoption, directly addressing key market challenges and bolstering Google Cloud’s position in this vital field.

    To learn more, download the free brief, The Future of BI With Looker and Gemini.

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  • Recapping AI Announcements from Google Cloud Next

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    Enterprise Strategy Group

  • Recapping Databases and Analytics Announcements from Google Cloud Next

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    Enterprise Strategy Group

  • Recapping Security Announcements from Google Cloud Next

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    Enterprise Strategy Group

  • Domo Drives AI Success With Data Products and AI Agents

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    Stephen Catanzano

    The data products market is experiencing rapid expansion, driven by the increasing need for organizations to leverage their data for AI, analytics, and business intelligence (BI) initiatives. AI initiatives, including AI agents, require more than raw data; they require packaged solutions that deliver actionable insights. Domo is a key innovator in this space, offering a platform that enables businesses to build sophisticated data products and AI agents. The Domo platform empowers users to create data-driven applications and visualizations, facilitating informed decision-making and driving business growth in an increasingly data-centric world.

    To learn more, download the free brief, Domo Drives AI Success With Data Products and AI Agents.

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  • Oracle Database 23ai Unifies Data for Generative AI

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    Stephen Catanzano

    The rapid rise of generative AI (GenAI) applications has created an urgent demand for modern data platforms capable of supporting diverse, complex, and high-volume data requirements. Organizations are increasingly turning to converged databases that can efficiently manage structured, semi-structured, and unstructured data in a unified environment. Oracle Database 23ai addresses this need by providing a comprehensive, mission-critical solution. By consolidating all data types and AI development capabilities into a single platform, Oracle empowers organizations to accelerate generative AI initiatives while ensuring data security, governance, and operational efficiency. At the recent Oracle Database Analyst Summit, several Oracle executives presented the latest innovations while customers shared how they use Oracle technology to support AI initiatives. We find that Oracle’s strategy aligns closely with our analysis of the role of databases in the generative AI market.

    To learn more, download the free brief, Oracle Database 23ai Unifies Data for Generative AI.

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  • The Future of SecOps in an AI-driven World

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    Dave Gruber

    Security operations (SecOps) is a mainstay of modern security programs. Once focused on reactive, alert-driven activities, today’s security operations have expanded to a risk mitigation function, inclusive of both proactive and reactive strategies like threat detection, response, and recovery. With such a broad scope of responsibility, it’s no surprise that the number and complexity of systems and technologies involved continue to grow, heavily influenced by the more recent explosion of generative AI (GenAI) adoption. TechTarget’s Enterprise Strategy Group recently surveyed IT and cybersecurity professionals to gain insights into these trends.

    To learn more, download the free infographic, The Future of SecOps in an AI-driven World.

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  • The Future of SecOps in an AI-driven World

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    Dave Gruber

    SecOps is a mainstay of modern security programs. Once focused on reactive, alert-driven activities, today’s SecOps has expanded to a risk mitigation function, inclusive of both proactive and reactive strategies like security posture management, core security controls optimization and tuning, detection and response, and recovery in the event of a harmful cyberattack. This expanded agenda has also increased collaboration with other functions, including risk management, IT, OT, software development and engineering, supply chain management, and more. With such a broad scope of responsibility, it’s no surprise that the number and complexity of systems and technologies involved continue to grow, heavily influenced by the more recent explosion of GenAI adoption.

    Despite all of this, for the first time in the past five years, this research indicates that the scales are tipping, as more organizations reported this year that SecOps is getting easier. This improvement is fueled by three industry mega-trends: tool consolidation, the application of GenAI within SecOps, and the effectiveness of XDR solutions.

    To gain further insights into these mega-trends and other developments in the security operations space, Enterprise Strategy Group surveyed 366 IT and cybersecurity professionals at large midmarket and enterprise organizations in North America (U.S. and Canada) involved with security operations technology and processes.

    Already an Enterprise Strategy Group client? Log in to read the full report. If you are not yet a Subscription Client but would like to learn more about accessing this report, please contact us.