Insight

  • Securing applications against exploit, denial of service, and other forms of cyberattack is a mission-critical goal for many cybersecurity teams today. However, due to the distributed nature of most IT environments, responsibility for application security involves a range of roles and teams such as those supporting cloud computing, on-premises technologies, networking, fraud, application development, and more. Recent research by Enterprise Strategy Group, now part of Omdia, investigated the degree of collaboration between these teams that contribute to the efficacy of the application security programs.

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  • Reaching a Tipping Point With API Security

    Application security has become more difficult in large part due to the wide range of tactics attackers can use to exploit their targets. APIs in particular have been a growing concern as applications become more interconnected and reliant on microservices. Recent research by Enterprise Strategy Group, now part of Omdia, found that API security vulnerabilities have not been receiving the attention and resources needed to appropriately mitigate growing threats, but that might be changing.

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  • 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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  • 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.

  • 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.

  • 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.

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  • The Future of BI With Looker and Gemini

    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.

  • Recapping AI Announcements from Google Cloud Next

  • Recapping Security Announcements from Google Cloud Next

  • Domo Drives AI Success With Data Products and AI Agents

    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.

  • Oracle Database 23ai Unifies Data for Generative AI

    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.