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.
Software development and data teams have historically been siloed. Yet with the rapid infusion of AI and generative AI code into software, this paradigm is brittle. JFrog has robust credentials as a unified enterprise software supply chain management specialist, but its recent moves into MLOps tell a bigger story beyond functionality.
The vendor continues to seek ways to facilitate business insight and productivity. Its latest Zoho Analytics release is notable for added capabilities in the data management and AI realms, helping to reach new groups of users and enable existing clients that operate the pipelines required to support analytical outcomes within the organization.
Organizations that do not leverage generative AI may fall behind, yet publicly available tools can expose sensitive business data, and companies often lack oversight over staff using GenAI products. Artificial Intelligence Risk is aiming to be the "safe" portal for enterprises. It seeks to provide a customizable environment where AI risk can be mitigated, and LOB productivity accelerated.
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