Insight

  • In the face of ransomware and other cybersecurity threats, organizations are concerned with cyber resilience, especially with the resilience of their sensitive data assets. For most organizations, data is a prime asset that drives core business processes, and in many cases, data is the business. Teams face unique challenges in their data resilience initiatives that typically combine data security posture management, data protection (recoverability), and data governance.

    To gain further insight into these trends, TechTarget’s Enterprise Strategy Group surveyed 370 IT professionals at organizations in North America (US and Canada) familiar with and/or responsible for data security, data protection, and data governance technologies in North America (US and Canada). This survey explored the volume and distribution of sensitive data, the most important data to protect, the automation of sensitive data discovery, data classification strategies, data resilience perceptions and strategies, data security posture management strategies, data resilience stakeholders, and spending plans.

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  • Generative AI (GenAI) has taken the world by storm since OpenAI introduced ChatGPT in late 2022, and it is widely considered one of the most potentially transformative technologies in many years. However, GenAI technology and the market ecosystem are evolving quickly, and many organizations are struggling to stay abreast of the constantly changing landscape. TechTarget’s Enterprise Strategy Group recently surveyed professionals involved in generative AI initiatives at their organizations to gain insights into these trends.

    To learn more about these trends, download the free infographic, The State of the Generative AI Market: Widespread Transformation Continues.

  • Private 5G: Inside the Progress and Opportunity

    As the rise of data users continues alongside the rapid proliferation of devices connected to enterprise networks, organizations are seeking ways to modernize their networks. Although advances with Wi-Fi have helped to support more demanding requirements in recent years, organizations are increasingly deploying private 5G networks alongside—or even in place of—traditional Wi-Fi installations. TechTarget’s Enterprise Strategy Group recently surveyed IT professionals involved with cellular or wireless technology and processes to gain insights into these trends.

    To learn more about these trends, download the free infographic, Private 5G: Inside the Progress and Opportunity.

  • Private 5G: Inside the Progress and Opportunity

    As the rise of data users continues alongside the rapid proliferation of devices connected to enterprise networks, organizations are seeking ways to modernize their networks. Although advances with Wi-Fi have helped to support more demanding requirements in recent years, organizations are increasingly deploying private 5G networks alongside—or even in place of—traditional Wi-Fi installations. The potential benefits of private 5G are vast, ranging from high performance, low latency, and extensive scalability to stronger security, customized deployment and control, and better support for emerging compliance and regulatory requirements.

    However, these potential benefits can come at the expense of numerous challenges as this technology shifts from nascency to the early stages of maturity. To gain further insights into these trends, TechTarget’s Enterprise Strategy Group surveyed 380 network IT professionals involved with cellular or wireless technology and processes at organizations in North America (US and Canada).

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  • Generative AI (GenAI) has taken the world by storm since OpenAI introduced ChatGPT in late 2022, and it is widely considered one of the most potentially transformative technologies in many years. However, GenAI technology and the market ecosystem are evolving quickly, and many organizations are struggling to stay abreast of the constantly changing landscape. As this nascent market emerges, organizations continue to seek guidance to help steer their deployments, asking: What are the emerging best practices? Which use cases are prevailing? How mature is the market, and how is this maturity defined? Is it best to build, buy, or partner? The ever-evolving nature of the answers to these questions creates a complex scenario for organizations that want to leverage GenAI technology.

    To gain further insight into these trends and challenges, TechTarget’s Enterprise Strategy Group surveyed 832 professionals at organizations across the globe involved in the strategy, decision-making, selection, deployment, and management of generative AI initiatives and projects at their organization and familiar with their organization’s use of third parties to support generative AI initiatives.

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  • Oracle Cloud World 2024 was an impressive showcase of cutting-edge advancements, particularly in the Oracle Database 23ai and artificial intelligence. The event delivered valuable insights and thought leadership, with one announcement standing out as a potential game changer: Oracle’s collaboration with AWS, which came after its announcements with Google Cloud and Microsoft Azure in the past year. This completes the circle and makes Oracle’s Autonomous Database and Oracle Exadata database capabilities available across these platforms. This strategic move is a significant shift for Oracle, enhancing its multi-cloud offerings and opening new opportunities for customers across these cloud ecosystems.

    This multi-cloud expansion holds tremendous benefits for both Oracle customers and those using AWS, Google Cloud, and Microsoft Azure. By making Oracle’s capabilities available, the company is empowering businesses with greater flexibility, enabling them to leverage the power of Oracle’s high-performance cloud solutions while maintaining their existing investments in other cloud providers. This partnership brings enhanced scalability, flexibility, and innovation. This will be particularly valuable for enterprises looking to integrate Oracle’s AI and database capabilities within their diverse cloud infrastructures while also taking advantage of each cloud’s AI capabilities, such as Amazon Bedrock, and easy access to all leading large language models (LLMs). AWS also offers a wide breadth of tools for generative AI development, which Oracle customers can leverage.

    Aside from the multi-cloud announcement, Oracle’s Database 23ai also introduced exciting new functionalities. Two areas of particular interest were the database’s vector capabilities and its ability to handle relational, graph, and document data models. The inclusion of vector search opens the door to more efficient and powerful AI-driven queries, making it easier to analyze and extract insights from large data sets. This is crucial in modern AI applications, where the ability to search and interpret data points quickly can drive better decisions and innovation with vectors offering advanced similarity capabilities.

    Vector databases, or databases with vector search capabilities, are increasingly becoming essential in the modern landscape of AI and machine learning. They enable the efficient processing of unstructured data, such as text, images, and complex data sets. They do this by transforming data into high-dimensional vectors, which can then be analyzed and searched using algorithms that calculate similarity between these vectors. The value of vector capabilities lies in their ability to perform similarity searches and provide contextually relevant results, which are crucial for AI models such as LLMs, image recognition systems, and recommendation engines. For example, in natural language processing applications, vector search can enable AI to find patterns and relationships between words, sentences, or documents based on meaning rather than just keyword matching. This means that AI can respond with more accurate and relevant information in everything from chatbot responses to complex business queries. At Oracle World, some impressive companies, such as PayPal and Deutsche Bank, shared their use of vector similarity capabilities in unique ways, such as vectorizing images and even support tickets to then use vector search to identify similar cases for comparison. This demonstrates vector capabilities beyond just AI use cases.

    For Oracle 23ai users, this translates into more powerful AI-driven solutions that can access and interpret vast amounts of unstructured data. Whether it’s finding relevant documents based on natural language queries, performing image similarity searches, or enhancing recommendation systems, vector search enables faster, more accurate insights. Additionally, it opens the door for better personalization and contextual understanding, which can be game-changing for industries like e-commerce, finance, and healthcare, where precision and relevance are key. In addition, Oracle 23ai’s flexibility to manage relational, graph, and document data in one database is highly valuable to developers and businesses. This unified approach simplifies the management of diverse data types, enabling organizations to harness their data more effectively for AI, machine learning, and advanced analytics. Oracle Cloud World 2024 demonstrated how Oracle pushes the boundaries of database technology and AI innovation while embracing a multi-cloud future.

  • In an era when IT operations teams are under tremendous pressure to accelerate processes, enable digital transformation, and reduce the unit cost and environmental impact of compute, AI can be a key enabling technology. Whether through generative AI (GenAI)-based tools, copilots, natural language querying, or advanced usage of causal and predictive AI, IT operations teams have an ever-increasing set of tools available to help them achieve their goals, improve stakeholder satisfaction, and optimize for their important metrics. TechTarget’s Enterprise Strategy Group recently surveyed IT professionals involved with observability, ITSM, and AIOps technologies and processes to gain insights into these trends.

    To learn more about these trends, download the free infographic, Generative AI in IT Operations: Fueling the Next Wave of Modernization.

  • Navigating Data Governance in the Age of AI

    Data from across organizational frameworks is pouring into AI tools and supportive components like LLMs, spawning increasing scrutiny driven by regulatory, compliance, and corporate governance requirements. To address these challenges, organizations are turning to data governance tools to help them carefully inspect, monitor, and manage data, especially in the face of widespread AI strategies and initiatives. TechTarget’s Enterprise Strategy Group recently surveyed data and IT professionals responsible for evaluating, purchasing, and managing data governance solutions and services to gain insights into these trends.

    To learn more about these trends, download the free infographic, Navigating Data Governance in the Age of AI.

  • Generative AI (GenAI) is a technology teeming with possibilities, and those extend to the realms of cybercrime and cyberdefense. Recent research by TechTarget’s Enterprise Strategy Group revealed some interesting findings when it comes to IT and cybersecurity professionals’ opinions on which side of the cybersecurity fight (i.e., adversaries or defenders) will benefit the most from GenAI, especially because organizational size and industry appear to influence their perspectives.

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  • Generative AI Governance Programs at Enterprises

    Teams across business lines and industries are excitedly ramping up generative AI (GenAI) initiatives in the pursuit of competitive advantage, operational efficiency, and more. However, this fast-paced technology deployment has cybersecurity and governance teams racing to keep up with GenAI use. Recent research by TechTarget’s Enterprise Strategy Group took stock of how these teams view GenAI technology and where they stand with implementing strong governance measures around it.

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  • The State of IT-driven Sustainability

    This Complete Survey Results presentation focuses on IT sustainability environments, perceptions and practices around sustainability, factors impacting and influencing purchases, the impact of AI, techniques for mitigating the impact of AI on sustainability, and stakeholder groups involved in and most impacted by sustainability initiatives.

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  • Navigating Data Governance in the Age of AI

    As a rapidly rising number of organizations across markets position data squarely at the heart of their business, data governance becomes a top priority amid regulations designed to ensure data privacy and security. Efforts to implement strong data governance and data quality are more difficult than ever as AI initiatives lean heavily on data to meet expectations for drastically improved processes and competitive advantages. Data from across organizational frameworks is pouring into AI tools and supportive components, including large language models (LLMs) and foundational models (FMs), spawning even more scrutiny driven by regulatory, compliance, and corporate governance requirements.

    To address these challenges, organizations are turning to data governance tools to help them carefully inspect, monitor, and manage data, especially in the face of widespread AI strategies and initiatives. To gain further insight into these trends, TechTarget’s Enterprise Strategy Group surveyed 318 data and IT professionals at organizations in North America (US and Canada) involved with or responsible for evaluating, purchasing, and managing data governance solutions and services.

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