PRESENTED BY

Sushant Kumar
Product Marketing
Manager

Chris Day
Director, APAC Sales 
Engineering
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What will you learn?

So you’re building a data lake to solve your big data challenges. A data lake will allow you to keep all of your raw, detailed data in a single, consolidated repository; therefore, your problem is solved. Or is it? Is it really that easy?

Data lakes have their use and purpose, and we’re not here to argue that. However, data lakes on their own are constrained by factors such as duplication of data and therefore higher costs, governance limitations, and the risk of becoming another data silo.

With the addition of data virtualization, a physical data lake, can turn into a virtual or logical data like through an abstraction layer. Data virtualization can facilitate and expedite accessing and exploring critical data in a cost-effective manner and assist in deriving a greater return on the data lake investment.

You might still not be convinced. Give us an opportunity and join us as we try to bust this myth! Join this Lunch & Learn as we explore the promises of a data lake as well as its downfalls to draw a final conclusion.

Spaces are limited; please ensure to register to save your seat.


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Spaces are limited. Please register to attend.

  • Online
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  • Thursday 25 February | 1:00pm - 2:00pm AEDT
  • Denodo ANZ
Agenda

  • Introduction to data virtualization
  • Use cases & customer case studies
  • Guided demonstration of Denodo Test Drive
  • Q&A
  • Online
    [Region - edit Event-Venue-Address-Line1 under My Tokens]
    _
  • Thursday 25 February | 1:00pm - 2:00pm AEDT
  • Denodo ANZ
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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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