Markets

Our seasoned analysts couple their industry-leading B2B research with in-depth buyer intent data for unparalleled insights about critical technology markets.

Overview

Business Applications

Cybersecurity

Data Management, Analytics & AI

Infrastructure, Cloud & DevOps

Services

Clients trust us across their GTMs—from strategy and product development to competitive insights and content creation—because we deliver high-quality, actionable support.

Overview

Insights

Browse our extensive library of research reports, research-based content, and blogs for actionable data and expert analysis of the latest B2B technology trends, market dynamics, and business opportunities.

Insights
Contact Us

Artificial Intelligence

  • Industries Dive Headfirst Into AI-enhanced Observability

    ·

    Torsten Volk

    Observability vendors are in a race to leverage AI to automate root cause analysis, enable self-healing, optimize resources, reduce alert noise, automate log analysis, and deliver contextualized actionable insights to end users. Organizations across industries recognize that implementing AI-enhanced observability tools can give them strategic insights that optimize the economics of their application development and platform engineering practices. However, Enterprise Strategy Group’s recent research reveals that an organization’s industry significantly influences three key aspects of AI-enhanced observability: the specific operational benefits realized, perceived return on investment, and how frequently teams override AI recommendations.

    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. 

  • Reinventing Data Loss Prevention: Adapting Data Security to the Generative AI Era

    ·

    Todd Thiemann

    Enterprises need to provide access to sensitive data while controlling against the unauthorized disclosure of that information from inadvertent leakage, insider threats, and outside attacks targeting data. Work-from-home and bring-your-own-device initiatives pose increased data loss prevention (DLP) challenges, and generative AI (GenAI) has opened new avenues for data leakage. Although DLP is a top investment category when it comes to data security, enterprises continue to struggle to classify data and control against data loss. Enterprise Strategy Group recently surveyed IT and cybersecurity professionals to gain insights into these trends.

    To learn more, download the free infographic, Reinventing Data Loss Prevention: Adapting Data Security to the Generative AI Era.

    Download Now

  • Reinventing Data Loss Prevention: Adapting Data Security to the Generative AI Era

    ·

    Todd Thiemann

    Enterprises need to provide access to sensitive data while controlling against the unauthorized disclosure of that information from inadvertent leakage, insider threats, and outside attacks targeting data. Work-from-home and bring-your-own-device initiatives pose increased DLP challenges, and new collaboration platforms and GenAI applications have opened new avenues for data leakage. Additionally, the proliferation of cloud services poses threats for data exfiltration, while intellectual property and trade secrets take new forms that do not lend themselves to conventional DLP solutions.

    Although DLP is a top investment category when it comes to data security, enterprises continue to struggle to classify data and control against data loss. Whether an enterprise DLP solution or DLP functionality within another security technology, current offerings generate considerable false positive alerts that distract teams that must evaluate and respond to such alerts. Existing approaches relying on regular expression (regex) rules can be brittle and require considerable maintenance, while current DLP solutions frequently encounter scaling and performance issues. Furthermore, complex data types like software code or health sciences data can be difficult to categorize.

    To gain insights into these trends, Enterprise Strategy Group surveyed 370 IT and cybersecurity professionals in North America (U.S. and Canada) involved with identity security technologies 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. 

  • Reinventing Data Loss Prevention: Adapting Data Security to the Generative AI Era

    ·

    Todd Thiemann

    This Complete Survey Results presentation focuses on how organizations categorize and protect data and control against data loss across the enterprise attack surface, which includes the challenges of preventing unauthorized disclosure of sensitive data, the risk posed by today’s data loss prevention (DLP) solutions, and the impact of cloud services and generative AI technologies.

    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. 

  • Messaging on AI-enabled Endpoint Benefits Needs to Mature

    ·

    Gabe Knuth

    The messages from vendors in the early days of AI PCs were focused on concepts like audio and video enhancement, real-time translation, and accessibility features (e.g., sign language interpretation, gesture-based controls, etc.). As the AI PC market matures, new light is shone on the success factors that organizations need to see to increase adoption, and recent research by Enterprise Strategy Group found that those features go far beyond basic AI functionality and value.

    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. 

  • Tool Consolidation and AI Push Cybersecurity Data Fabrics Forward

    ·

    Tyler Shields

    Today’s cybersecurity teams encounter issues such as fragmented tools, siloed data, and increased operational complexity, reducing their effectiveness in managing business and technology risks. Recent findings from Enterprise Strategy Group show a shift toward tool consolidation and the integration of cybersecurity data security fabrics and comprehensive platforms to tackle these challenges. This brief examines how consolidation and the emergence of AI capabilities are pushing the adoption of data fabrics.

    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. 

  • Industries Vary Navigation Routes Through Data Readiness Requirements

    ·

    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.

    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. 

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

    ·

    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.

    Download Now

  • Data Complexity Inhibits Large Midmarket Organizations Along Their AI Journey

    ·

    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

    ·

    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.

    Download Now

  • Domo Drives AI Success With Data Products and AI Agents

    ·

    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.

    Download Now

  • Oracle Database 23ai Unifies Data for Generative AI

    ·

    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.

    Download Now