PRESENTED BY
Elaine Chan
Regional VP, Sales, ASEAN & Korea
Chris Day
Director, APAC Sales Engineering
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About the Session

In the recent Building the Unified Data Warehouse and Data Lake report by leading industry analysts TDWI, we discovered 64% of organizations stated the objective for a unified Data Warehouse and Data Lakes is to get more business value and that 84% of organizations polled felt that a unified approach to Data Warehouses and Data Lakes was either extremely or moderately important.

During this webinar, we will discuss how applying a logical data fabric and the associated technologies of machine learning, artificial intelligence, and data virtualization reduce time to value. Hence, increasing the overall business value of your data assets.

Attend & Learn:

  • How a Logical Data Fabric is the right approach to assist organizations to unify their data.
  • The advanced features of a Logical Data Fabric that assist with the democratization of data, providing an agile and governed approach to business analytics and data science.
  • How a Logical Data Fabric with Data Virtualization enhances your legacy data integration landscape to simplify data access and encourage self-service.

Spaces are limited and prioritised for ASEAN region attendees. Please register to attend.

  • Online

  • 23 November 2021 | 1.00pm - 2.00pm SGT
  • Denodo ASEAN
Agenda

1.00pm - 1.20pm: Building a Logical Data Fabric using Data Virtualization

1.20pm - 1.50pm: Denodo Demo

1.50pm - 2.00pm: Q&A / Next Steps

2.00pm: End of Session

  • Online

  • 23 November 2021 | 1.00pm - 2.00pm SGT
  • Denodo ASEAN
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Denodo is a leader in data management. The award-winning Denodo Platform is the leading logical data management platform for transforming data into trustworthy insights and outcomes for all data-related initiatives across the enterprise, including AI and self-service. Denodo's customers in all industries all over the world have delivered trusted AI-ready and business-ready data in a third of the time and with 10x better performance than with lakehouses and other mainstream data platforms alone.
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