Introducing the Featured Speakers for "Data Virtualization" on April 11th
Phil is President and CEO of Cadeon Inc., an international Big Data, Analytics and IoT company, headquartered in Calgary. He is also an Entrepreneur, known for his thought leadership in Enterprise Architecture, and his community contribution and support. A former Chief Enterprise Architect now focused on leveraging the Exponential Growth in information to build and grow his business and provide Cadeon’s customers a Framework to digitally transform their businesses.
Niaz Tadayyon, Business Analytics Practice Lead, Cadeon Inc.
Niaz is Business Analytics Practice Lead at Cadeon Inc. based in Calgary Leads consulting engagements to deliver high-value analytical solutions to provide business values to our clients. She has over 16 years of international experience in Advanced Analytics, Enterprise Architecture and Business Intelligence. She has contributed to the success of large and complex applications, data integrations, Business Intelligence and Predictive Analytics solutions. She also teaches at the University of Calgary.
“The Rise of Data Virtualization and the Fading Glory of ETL” - A Data Virtualization Case Study presented by Cadeon
by Phil Unger & Niaz Tadayyon
Please join us as Phil Unger and Niaz Tadayyon from Cadeon present a case study of using Data Virtualization to stitch together data from multiple clouds and maintain a single unified source of this data. In this discussion we will define what data virtualization is, compare and contrast to ETL and provide a demo and sample use case of the many benefits including speed to market, savings in time in money, and many more.
Data virtualization is not new. It has been around for many years in a number of different guises, including enterprise information integration and data federation. It is only recently, however, that the approach has gained the recognition and success it deserves.
The feature of data virtualization (DV) that frequently goes unnoticed lies in its ability to provide IT and business users with a single high-level view of data that may be spread throughout the enterprise.This capability can dramatically simplify access to data for less experienced users.
The other thing we like about DV is the ability to hide complexity from the data consumers by abstracting and federating the source data making data sources independent of the data consumers.This allows IT to swap-out source systems without having to rewrite any reports or visualizations.