Data Governance & Data Quality – A foundation to enable your organization’s AI/ML strategy

On Demand
Presented by:
Guidehouse

Guidehouse is a client-centered, mission-driven organization focused on solving today's most complex issues facing our clients and our world through collaborative solution design, bold strategy, and innovation that advances conventional thinking.

Featured Speakers

  • Robert Audet, Partner, Data Management at Guidehouse
  • Jonathan Shiery, Partner, Financial Services at Guidehouse

Few organizations can refute the potential value associated with using artificial intelligence to cut costs, boost revenue, and stay competitive. According to the OECD’s recent report on AI, ML, and Big Data in finance, global spending on AI is forecast to double for 2020-24, growing from $50 billion to more than $110 billion over four years. However, research shows that few organizations have data they can trust to have AI algorithms produce reliable results.  Poor quality or unreliable data makes up a large chunk of many companies’ historical data, which often was “acquired haphazardly” and may “lack the detail and demonstrable accuracy needed for use with AI and other advanced automation,” as noted in a research report by the Wall Street Journal. The incentives to fix these and other data issues are significant. Researchers at the University of Texas have estimated that increasing data usability by 10% would boost annual revenue for Fortune 1000 companies by more than $2 billion.

 

Join this discussion to explore what leading Financial Institutions are doing to improve their data by maturing data governance and quality capabilities to enable AI and stick around for Q&A at the end!

 

Agenda:

  • 12:00pm- 12:30: Featured Presentation
  • 12:30-1:00pm: Your Q&A and interaction

About Enterprise Data & AI:

The Enterprise Data & AI Community is geared toward innovative companies pushing the boundaries of what’s possible with Artificial Intelligence and cognitive technologies. This community is focused on the enterprise data side of AI including: Data Engineering, Data Preparation, Data Labeling & Annotation, Sourcing and Generating Data, and All Other Topics Data-Related and AI

Featured Presenters

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