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HP StorageWorks 4400 Enterprise Virtual Array (EVA4400) Performance by Hewlett-Packard Company
August 2008 - (Free Research) In this white paper learn how sequential performance provides customers with improved data transfer rates for applications such as data warehousing, streaming video, high-performance technical computing, and backups and restores.
Business Intelligence Solutions for SAP by Business Objects
September 2008 - (Free Research) This report is designed for technical executives who wish to understand the many options that are available today for building or buying a business intelligence solution for an SAP-centric organization.
Advances in Data Warehouse Performance by IBM.
August 2008 - (Free Research) Learn how DB2 can help you meet the demands of business intelligence by reducing query response time from hours to seconds, supporting real time data warehousing, optimizing your storage and lowering operating costs.
Speeding ETL Processing in Data Warehouses by SyncSort
August 2008 - (Free Research) This white paper discusses how two operations in particular -- joins and aggregations -- play an integral role during preprocessing as well in manipulating and consolidating data in a data warehouse.
DaaS™: Data Warehousing as a Service by Kognitio
July 2008 - (Free Research) Data warehousing as a Service (DaaS) is an extremely attractive proposition to mid-size companies, as well as departmental divisions of large corporations that seek to implement cost-effective, quick and dynamic data analytics projects.
Logs: Data Warehouse Style by LogLogic, Inc.
September 2008 - (Free Research) The LogLogic Log Management Data Warehouse enables organizations to centralize log data for easy, efficient access -- ensuring IT security, regulatory compliance, and operational efficiency.
Oracle Database 11g for Data Warehousing and Business Intelligence by Oracle Corporation.
August 2008 - (Free Research) This white-paper provides an overview of Oracle Database 11g’s capabilities for data warehousing, and discuses it’s key features and technologies. Discover how to integrate information, perform fast queries, scale to very large data volumes, and more.
Is a Data Warehouse the Only Option for Business Intelligence? by Information Builders Inc.
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October 2007 - (Free Research) While data warehouses are important for many types of analytical systems, they aren’t always necessary. Building a data warehouse can dramatically increase the cost of a BI project. This paper describes data warehouses, along with many other options for placing relevant, timely information in the hands of business users.
Datanomic Business Intelligence and Data Warehousing by Datanomic.
By using dn:Director to improve data quality and isolate data that is unreliable, organizations are able to optimize the return on investment in BI and Data Warehousing and maximize competitive advantage.
A Broad Information Reach: The Gateway to Information Management by Cognos, an IBM Company
September 2008 - (Free Research) The first key to realizing the potential of your data is implementing a solution built for open data access, ensuring a broad information reach. This paper explains why this is the essential starting point for accessing, integrating, and organizing data.
Essential Steps for the Integrated EDW by Informatica Corp.
September 2008 - (Free Research) This white paper proposes a specific architecture for building and integrated enterprise data warehouse (EDW) that directly supports master data management efforts and provides the platform for consistent business analysis across the enterprise.
IntelliPRINT Dashboard Reporting by Synaptris, Inc.
August 2008 - (Free Research) Reporting 2.0 is the new web-based enterprise reporting where end-users can create, interpret, and extend their reports or analyze report data in real-time with no IT overhead. Learn more about it in this whitepaper.
Optimizing ETL for demanding data environments by SyncSort
October 2008 - (Free Research) View this Webcast and complimentary Podcast to learn more about how to use ETL today to optimize demanding data environments as well as when and how ETL can effectively support near-real-time requirements.
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