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Expert Best Practices: Data Management Strategies for AI

February 20, 2024

Prerequisite: None

Deanne Larson, Ph.D.



Larson & Associates

In today's data-driven landscape, the success of machine learning (ML) and artificial intelligence (AI) initiatives hinges on robust data management strategies.

This session will focus on key aspects of data management strategies for ML/AI, addressing critical topics such as data quality, preparation, and integration. This session will review harnessing the power of data lakes, data warehouses, and data catalogs to fuel your ML/AI initiatives.

Topics to include:

  • Discover techniques to assess and elevate data quality, ensuring trustworthiness and reliability for your ML and AI initiatives
  • Optimize your data sets for high-performing ML models through effective data preprocessing and transformation
  • Understand how to strategically use data lakes, data warehouses, and data catalogs to support your ML and AI objectives
  • Learn to design and manage efficient data pipelines that ensure a smooth data flow from source to model
  • Master the art of feature engineering to enhance the predictive power of your ML models

Agenda Key

  • Analyst Insights: the latest trends and research delivered by TDWI analysts.
  • Expert Best Practices: experts, with in-the-trenches expertise, focus on best practices and successful real-world applications
  • Curated Case Studies: case studies, delivered by experts in the field, with a focus on actionable takeaways
  • Tech-in-Action: moderated technology demos and case study sessions that enable attendees to assess all the latest AI applications and technologies
  • Workshop: Interactive session where leaders come together with peers, with an expert facilitator, to discuss common challenges and proven best practices

Register Online

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TDWI Las Vegas

Planet Hollywood Las Vegas Resort & Casino Hotel
Las Vegas, NV
February 19–23