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The Data Mesh architectural design was first proposed in 2019 by Zhamak Dehghani, principal technology consultant at Thoughtworks, a technology company that is closely associated with the development of distributed agile methodology. A data mesh is a distributed, de-centralized data infrastructure in which multiple autonomous domains manage and expose their own data, called “data products,” to the rest of the organization.
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As a company steeped in research and development, Pierre Fabre Laboratories manages large volumes of data, and since 1998, the pharmaceutical multinational has relied on a traditional, on-premises data warehouse for this purpose.
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Autodesk created a single, unified enterprise access point for any data used within the company by using Denodo data virtualization as a logical data warehouse.
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Your business stakeholders need more data, faster data, more relevant, and more timely data. They are pushing for a data and analytics self-service model to speed up getting key insights. The CEO has made it clear that this is critical to the continued growth and health of the business...this is your top priority.
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Presented at Digital Gov and Cloud Summit 2021Data Virtualisation is a logical data layer that virtually integrates all the data siloed across the disparate systems in an organisation, what-ever its format or structure. This presentation outlines how public sector organisations can leverage data virtualisation to:
https://www.denodo.com/en/webinar/technological-solutions-maximising-true-potential-your-data-assets
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Panel by François Gaudreau, National Lead-Intelligent Automation at KPMG; Inessa Gerber, Director of Product Management at Denodo; and moderated by Robert Eckersley, Director, Partner and Channels Sales at Denodo.
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Paul Shimabukuro, Sales Engineer for Denodo, gives a product demonstration of Denodo Platform with a particular focus on how data virtualization enables data as a service.Watch this demo to learn:
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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?
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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?
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How to Prepare for the Denodo Platform 8.0 Certified Developer Professional Exam
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