Paige is a Senior Research Analyst for the Data, AI & Analytics Channel at 451 Research, a part of S&P Global Market Intelligence, covering core data management topics. Key themes include data privacy, data governance, data integration, metadata management, data quality and master data management. She has experience covering a broad range of technologies spanning the Data, AI & Analytics stack, from databases to self-service analytics.
In her current research, Paige is analyzing the need for information governance to maximize the value of enterprise data amid proliferating global regulatory requirements and rising consumer expectations for data stewardship. With data privacy and compliance as a specialty focus, Paige explores how the enterprise can align technical requirements with business strategy, enabling more profitable and compliant leverage of data.
Early in her career, Paige worked on the vendor side, providing marketing and strategy for ZL Technologies, an information governance provider that specializes in the management of unstructured data for compliance, legal and archiving needs. Prior to working at 451 Research, she was a Senior Analyst at Ovum (now Omdia).
Paige received her Bachelor of Science degree in psychology and neuroscience from Duke University, and a Master of Management Studies (MMS) degree from the Duke University Fuqua School of Business.
There is a conundrum in the AI era: try new technologies and incur risk, or wait and fall behind. Cloudera aims to be a trustworthy business partner in this era by providing the architecture allowing the building of and experimentation with AI, as well as embedding AI within the enterprise software itself.
This report highlights some of the key topics we expect to be prominent in 2024 in the data, AI and analytics sectors. Generative AI obviously takes the headlines, but for the technology to succeed, preexisting issues around data management, data operationalization (DataOps), machine learning operationalization (MLOps) and other infrastructure-related tasks need to be solved.
The company, with a rich heritage in iPaaS architecture and API management, feels poised to capture the force of the enterprise AI zeitgeist by providing a solid basis for ongoing data management as well as embedded AI-driven software features. Its ongoing Boomi World Tour 2023 touted this philosophy at a recent stop in Silicon Valley.
The company is motivated by a fundamental disconnect: that our experiences as consumers and citizens happen in real time, yet most business IT and data systems are still designed for batch processing. At its second annual Current 2023 conference, Confluent emphasized these opportunities and challenges.
Enterprise initiatives around AI require transparency and visibility of data. A big part of that visibility is establishing comprehensive provenance for data that can span diverse systems. By reaching for data lineage vendor Manta, IBM is looking to augment the trust and transparency offered by its watsonx platform ecosystem.
In the data-driven experience economy, trust is foundational for both customers and businesses, and the use of generative artificial intelligence has only accelerated this requirement. At Dreamforce, Salesforce emphasized the role of trust both architecturally, in terms of product and data, and ethically, in terms of corporate position.
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