Logical Data Fabrics to the Rescue

Robin Tandon
Director of Product Marketing
Bhavita Jaiswal 
Sales Engineer
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What will you learn?

 In this webinar we will be discussing the benefits of creating a logical data fabric and why data fabrics in general are the only successful modern architecture for data integration projects. We will learn how a logical data fabric smooths away the challenges of all of the competing data architectures business users, data scientists and other data consumers come across when interfacing with disparate data sources in data lakes, data hubs, data warehouses and other data silos.

These include :-

  • How a data fabric; a popular new architectural approach integrates with existing transactional data and data delivery systems to make all the individual components look as one in particular
  • Benefits of decoupling the consumption layer from the data sources and why this has many business benefits
  • key attributes of a logical data fabric including centralized data security, embedded meta data support, built-in support for record-oriented and set-oriented data access, and AI support

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

Agenda
  • Introduction 
  • Presentation- Logical Data Fabrics to the Rescue
  • Q&A


Register to attend

  • Online
    India
    _
  • Dec 16, Thursday | 2.30pm - 3pm (IST)
  • Denodo
Agenda
  • Introduction to data virtualization
  • Use cases & customer case studies
  • Guided demonstration of Denodo Test Drive
  • Q&A
  • Online
    India
    _
  • Dec 16, Thursday | 2.30pm - 3pm (IST)
  • Denodo
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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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