Datawarehouse White Papers

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Put your Analytics Applications into Overdrive
sponsored by IBM
WHITE PAPER: With IBM Informix Warehouse and the Intel Xeon processor E7 family, IBM and Intel are partnering to deliver superior performance for in-memory analytics processing – helping you turn massive amounts of data into business opportunities.
Posted: 30 Aug 2013 | Published: 31 Dec 2012

IBM

Customers Achieve Extreme Performance at Lowest Cost with Oracle Exadata Database Machine
sponsored by Oracle Corporation
WHITE PAPER: This reference contains a sampling of real business results that organizations in a variety of industries have achieved by implementing Oracle Exadata. Learn how you can use Oracle Exadata to reduce IT costs through consolidation, manage more data on multiple compression tiers, improve the performance of all applications and much more.
Posted: 06 Mar 2012 | Published: 18 May 2011

Oracle Corporation

Data Mart Consolidation
sponsored by Hexaware Technologies
WHITE PAPER: This white paper explores how Data Mart consolidation is an effective tool for saving money when dealing with large volumes of data.
Posted: 12 Sep 2011 | Published: 12 Sep 2011

Hexaware Technologies

MDM and Data Quality for the Data Warehouse
sponsored by Informatica
WHITE PAPER: This executive brief explains how the combination of master data management (MDM) and data quality (DQ) can significantly enhance the accuracy and reliability of data, enabling timely, confident decisions and accurate reporting.
Posted: 26 Mar 2014 | Published: 31 Dec 2013

Informatica

Red Hat JBoss Data Grid: The Perfect Solution for Big Data and Application Performance
sponsored by Red Hat
WHITE PAPER: Big data requires real-time access to data, scalability, and non-disruptive technology - qualities that relational databases just don't have. In this resource, discover how an in-memory data grid (IMDG) addresses the challenges posed by big data and application performance, and learn how one particular data grid can benefit your IT department.
Posted: 07 Jun 2013 | Published: 30 Jun 2012

Red Hat

Cost/Benefit Case for IBM PureData System for Analytics: Comparing Costs and Time to Value with Oracle Exadata Database Machine X3
sponsored by IBM
WHITE PAPER: In this white paper, see how expert solutions stack up and learn how to choose which hardware best suits your organization based on the nature of organizational informational architectures, trade-offs between compatibility with existing software and skills, the speed of new application deployment, and costs.
Posted: 22 Nov 2013 | Published: 31 Aug 2013

IBM

7 must-have capabilities of big data DBMS
sponsored by IBM
WHITE PAPER: Companies are rushing to invest in big data analytics tools, but many forget about the underlying infrastructure that supports their big data efforts. In this informative white paper, learn why the right database management system (DBMS) could be the key to a successful big data analytics project.
Posted: 07 Apr 2014 | Published: 28 Feb 2014

IBM

Building a Trusted SAP HANA Data Center
sponsored by Cisco and SAP
WHITE PAPER: In this comprehensive resource, explore a variety of hardware appliances that are SAP-approved as platforms for HANA. Discover how these appliances from Cisco, EMC, and VCE can benefit your SAP HANA implementation, and evaluate how they stack up against the five essential characteristics of a SAP HANA hardware platform.
Posted: 22 Apr 2014 | Published: 22 Apr 2014

Cisco and SAP

A foundation for database simplification, consolidation and cost reduction
sponsored by IBM
WHITE PAPER: This white paper challenges the x86 processor trend, demonstrating that modern mainframe technology represents a scale-up option to the current racks filled with blades. It looks at the way organizations can benefit in terms of improved agility, increased reliability and cost savings by consolidating Oracle databases onto IBM’s zEnterprise.
Posted: 14 Feb 2012 | Published: 14 Feb 2012

IBM

Transforming Big Data Into Insights - IBM System
sponsored by IBM
WHITE PAPER: Learn what requirements are needed to accommodate big data analytical workloads, and how infrastructures must change.
Posted: 20 Jan 2014 | Published: 31 Oct 2013

IBM