Showing 1 - 10 of 29 pages tagged with: Logical Data Warehouse
By Independent Industry Analyst Rick van der LansOrganizations can no longer afford to rely on a traditional data warehouse solution to support new business intelligence (BI) requirements along with their existing BI workloads. The rigid development, operation, and management process that characterizes traditional solutions is insufficient to support new BI requirements such as fast and agile report development, investigative analytics, data science and self-service BI.
The Logical Data Warehouse (LDW), a data system encompassing concepts of a traditional data warehouse, includes data from disparate data sources and core data warehouses.Read this eBook for a complete understanding of the LDW, especially regarding common architectural patterns, performance considerations, governance, self-service discovery, and customer success stories.
Drillinginfo uses data virtualization to manage and quickly provision data to the product development team and its customers. Drillinginfo will present how they have created a virtual data abstraction layer using data virtualization and reduced creation of web services for application development time from 1 – 2 weeks to less than a day.
Data is treated truly as an asset at Guardian Life. We have created a Data Services Marketplace which contains valuable data from the underlying sources and is used by business users for day-to-day operations. In this presentation we will talk about how Data Virtualization can be used to support the marketplace with real-time data services, provision non real-time data into Hadoop, and swap underlying sources without effecting business users.
CIT modernized its data architecture in response to intense regulatory scrutiny. They will present how data virtualization is being used to drive standardization, enable cross-company data integration, and serve as a common provisioning point from which to access all authoritative sources of data.
Data virtualization is an agile technology that can be deployed for multiple use cases within a company. In this presentation, Intel will present their journey, starting small and growing Data Virtualization to an Enterprise IT enabling use cases such as samples management, cloud, and big data for sales and marketing.
IT organizations find several challenges when responding to business needs. Data integration is paramount and this talk describes three different paradigms: using client-side tools, creating traditional data warehouses and the data virtualization solution - the logical data warehouse, comparing each other and positioning data virtualization as an integral part of any future-proof IT infrastructure.
This session will explore key features in the Denodo Platform that help with the common challenges found in large deployments: hundreds of developers, thousands of queries, and multiple environments. The features that will be highlighted include integration with version control systems, metadata synchronization and migration, monitoring and diagnosing, and resource management.
In this presentation, executives from Denodo preview the new Denodo Platform 6.0 release that delivers Dynamic Query Optimizer, cloud offering on Amazon Web Services, and self-service data discovery and search. Over 30 analysts, led by Claudia Imhoff, provide input on strategic direction and benefits of Denodo 6.0 to the data virtualization and the broader data integration market.