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TAG REFERENCES

Showing 1 - 5 of 5 pages tagged with: Data Warehouse
Modernizing Data Architecture using Data Virtualization for Agile Data Delivery
In this session, Dave Kay, Data Consultant within the Analytics and Architecture group at Zurich Insurance, explains how Zurich is modernizing their data infrastructure using data virtualization to accelerate delivery of mortgage insurance and intra-day operational reports to business analysts, salespeople, underwriters, managers, and actuarial staff.
Extended Data Warehouse - A New Data Architecture for Modern BI
SpeakersDr. Claudia Imhoff, President, Intelligent Solutions & Founder, Boulder BI Brain TrustPaul Moxon, Senior Director, Product Management, Denodo TechnologiesSummaryBig Data, Internet of Things, Data Lakes, Streaming Analytics, Machine Learning…these are just a few of the buzzwords being thrown around in the world of data management today. They provide us with new sources of data, new forms of analytics, and new ways of storing, managing and utilizing our data. The reality however, is that traditional Data Warehouse architectures are no longer able to handle many of these new...
Data Warehousing & BI Summit (The Netherlands)
Denodo is sponsoring the Data Warehousing & BI Summit, the International Conference on Data Warehousing & Business Intelligence with top rated speakers such as Claudia Imhoff, Rick van der Lans, Colin White and Mike Ferguson. We will be presenting our data virtualization platform in our booth, and we will also be hosting a conference showing how data virtualization can help organizations to manage their data.
Data Virtualization and ETL
A question that is frequently asked is “when should I use data virtualization and when should I use ETL tools?” Other variants of this question is “does data virtualization replace ETL?” or “I’ve already got ETL, why do I need data virtualization?”  This Denodo Technologies architecture brief will answer these questions. Extract, Transform, and Load (ETL) is a good solution for physical data consolidation projects which result in duplicating data from the original data sources into an enterprise data warehouse (EDW) or a new database. This includes:
Data Virtualization Usage Patterns for Business Intelligence/ Data Warehouse Architectures
Today’s users demand reports with better business insights, more information sources, real-time data, more self-service and want these delivered more quickly, making it hard for the BI professionals to meet such expectations. This white paper outlines how the use of Data Virtualization can help BI professionals to accomplish these goals.