Big 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 technologies and a new data architecture is required.
So what does the new architecture look like? Does the enterprise data warehouse still have a role? Where do these new technologies fit in? How can business users easily and quickly access the various sources of data and analytic results at the right time to make the right decisions in this new world order?
Watch this webinar, featuring Dr. Claudia Imhoff, who addresses these questions and presents the Extended Data Warehouse architecture (XDW), demonstrating the need for each component and how an enterprise combines these into appropriate workflows for proper decision support.
Attendees will learn:
* The new analytical and technical components in the Extended Data Warehouse.
* The use cases for each of these components.
* The best practices and considerations involved in the implementation of the XDW.
* The important role of data virtualization and associated case studies demonstrating its usage.
So what does the new architecture look like? Does the enterprise data warehouse still have a role? Where do these new technologies fit in? How can business users easily and quickly access the various sources of data and analytic results at the right time to make the right decisions in this new world order?
Watch this webinar, featuring Dr. Claudia Imhoff, who addresses these questions and presents the Extended Data Warehouse architecture (XDW), demonstrating the need for each component and how an enterprise combines these into appropriate workflows for proper decision support.
Attendees will learn:
* The new analytical and technical components in the Extended Data Warehouse.
* The use cases for each of these components.
* The best practices and considerations involved in the implementation of the XDW.
* The important role of data virtualization and associated case studies demonstrating its usage.
- Category
- Management
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