Paige Bartley is a senior research analyst at S&P Global Market Intelligence. She leads the data management research within the 451 Research Data, AI & Analytics channel and frequently contributes to the Information Security channel. Covering the technologies that compose the “plumbing” of the data and analytics stack, Paige examines the flow and control of data within organizations, as well as how organizations can better align their business functions and technology. Paige came to S&P Global Market Intelligence through its 2019 acquisition of 451 Research, which she joined in 2018. Prior, she held a senior analyst role with Ovum (now Omdia), researching similar topics in enterprise data management and analytics. She began her career on the vendor side, working in marketing and strategy for an unstructured data governance specialist. Data privacy operations (PrivacyOps) and data governance are areas of specialty, particularly regarding how these initiatives can be linked to customer experience and profitability outcomes. Other areas of concentration include AI, data integration, metadata management, data quality and data observability, and master data management. Broader concepts include enterprise data culture, digital rights and data ethics. Paige holds a BS in psychology and neuroscience from Duke University and a Masters of Management (MMS) from the Duke University Fuqua School of Business.
Being able to comply with regulatory mandates is a major business consideration and challenge, particularly for multinational companies. In a tumultuous 2024 US election cycle, many organizations were concerned about how the future regulatory landscape would affect them. But the more things change, the more they stay the same.
Obtaining credentials and demonstrating ongoing compliance can be difficult, especially for small firms. Vanta proposes that clients can accelerate sales cycles and enhance revenue recognition via technology that provides a proactive lens into compliance posture, aided optionally by AI.
This report highlights the key topics we expect to be prominent in 2025 in the data, AI and analytics space. While generative AI remains a predominant theme, for the technology to succeed, preexisting issues must be resolved around data management, data operationalization, machine learning operationalization and other infrastructure-related tasks.
The company has long hung its hat on enhanced content security, governance and compliance capabilities for business use. At its annual BoxWorks event, Box led with an "intelligent content management" narrative, and announced several new AI, business process and data protection and compliance capabilities.
Enterprises typically have the talent and tools to secure their data and customize their architecture related to GenAI and LLMs. Consumers rarely have these resources. Data fed into consumer-facing GenAI tooling is often used to train models that benefit other users. That data cannot be extracted back out, creating privacy challenges.
The ability to consistently combine, access and query diverse data sources is critical to business insight efforts. Historically known as a data virtualization specialist, Denodo is now expanding its product vision with a more comprehensive data management approach to accelerate data-driven business outcomes in an era driven by AI use cases.
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