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Showing 1 - 10 of 11 pages tagged with: Logical Data Warehouse
Developing a Bimodal Logical Data Warehouse Architecture Using Data Virtualization
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.
Autodesk
Business NeedAutodesk decided to transform its revenue model from a conventional perpetual licensing model to a subscription-based licensing model. Autodesk’s infrastructure was set up for managing the perpetual licensing model and was unable to meet the demands for business information and agility required to meet their transition to a new licensing model.The SolutionAutodesk needed an agile BI 2.0 architecture with a logical data warehouse at its core to track subscriptions, renewals, and payments. Data virtualization helped Autodesk integrate new transactional systems that manage...
Kadenza Announces Strategic Partnership with Denodo and Launches Logical Data Warehouse Solution
LAREN, HOLLAND - November 3, 2015 - Today Kadenza announced its strategic partnership with Denodo, the leader in data virtualization software. Using the Denodo Platform as the core solution, Kadenza plans to offer a logical data warehouse solution, which will enable its customers to efficiently provide deeper insights across all enterprise data sources while flexibly reacting to changes.
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.
Succeeding with - Data Virtualization: Part 1 – High Value Use Cases for Analytical Data Services
Analytical or informational use of virtual data services produce integrated information for reporting, dashboards, CPM scorecards and analysis from multiple underlying heterogeneous data sources. This data can be used to support decisions made by executives, line managers, front-line staff and external users. They may also integrate historical and live operational data (sometimes referred to as an extended data warehouse pattern) for a holistic view of business activity to support specific business tasks e.g. 360 degree view of the customer for sales. Data sources may include relational...
Implementing Data Virtualization for DW and MDM Extensions (NA)
The ongoing evolution of business requirements and growth of data volumes continue to put added challenges on existing DW and MDM implementations. Challenges that in many cases cannot be met. Data Virtualization compliments existing DW, MDM and other architectures and business initiatives, providing the agility and flexibility - at a lower cost – for the enablement of Virtual MDM, self-service BI, operational BI, rapid prototyping and real-time analytics.Attend & Get Unique Insights into:How Data Virtualization can provide a simple and low cost alternative to traditional DW and MDM...
Implementing Data Virtualization for DW and MDM Extensions (EMEA)
The ongoing evolution of business requirements and growth of data volumes continue to put added challenges on existing DW and MDM implementations. Challenges that in many cases cannot be met. Data Virtualization compliments existing DW, MDM and other architectures and business initiatives, providing the agility and flexibility - at a lower cost – for the enablement of Virtual MDM, self-service BI, operational BI, rapid prototyping and real-time analytics.Attend & Get Unique Insights into:How Data Virtualization can provide a simple and low cost alternative to traditional DW and MDM...
Broad Spectrum Data Virtualization: an Introduction
Data Virtualization is becoming mainstream. In its new evolution, instead of being pitched as an alternative to ETL/replication, it has been co-opted to provide Agile BI/Logical DW and integration of Big Data analytics. This session will talk about why broad spectrum data virtualization is different – from data sources, modeling virtual data, publishing data services, security and governance, intelligent high performance, and flexible query execution — and why all this is important to meet future business needs that smash together BI & Big Data Analytics with modern Application and...