Unlocking the business value of unstructured data with AI and ML

Whitepaper
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The combination of AI and machine learning is no longer a glimmer on the technological horizon. This paper from 451 Research explains how organizations can exploit the potential opportunities of AI.

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About this paper

A Pathfinder paper navigates decision-makers through the issues surrounding a specific technology or business case, explores the business value of adoption, and recommends the range of considerations and concrete next steps in the decision-making process.

ABOUT THE AUTHOR

MATT ASLETT
RESEARCH VICE PRESIDENT

Matt Aslett is a Research Vice President with responsibility for 451 Research’s Data, AI and Analytics Channel – including operational and analytic databases, Hadoop, grid/cache, stream processing, data integration, data governance, and data management, as well as data science and analytics, machine learning and AI. Matt’s own primary area of focus currently includes distributed data management, data catalogs, business intelligence and analytics, data science management, and enterprise knowledge graphs.

PAIGE BARTLEY
SENIOR ANALYST, DATA MANAGEMENT

Paige is a Senior Analyst for the Data, AI and Analytics channel at 451 Research, covering data management, including data integration, data governance, data quality and master data management. She has experience covering a broad range of information management technologies spanning database functionality and self-service analytics to regulatory policy and compliance.

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Artificial Intelligence (AI) and Machine Learning (ML) are on the path to become one of the most transformational technologies we have seen to this day. Whether we realise it or not, AI & ML are revolutionising the way we work, study, travel, govern, consume and pursue activities in our everyday lives.

In a whitepaper with 451 Research, we discuss how AI & ML can unlock information from data, driving business value and reshaping day-to-day functions.

The paper discusses:

  • What AI is and how it works
  • The enterprise impact of AI and ML
  • Barriers to AI and ML adoption
  • Real world use cases

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