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Microsoft® SQL Server® 2008 R2 Parallel Data Warehouse and Fast Track Data Warehouse Run on Intel® Xeon® Processors by Intel and Microsoft

March 29, 2011 - (Free Research)
Microsoft and Intel are now ready to help organizations turn a new page in data warehousing. Using Microsoft® SQL Server® 2008 R2 Enterprise, you can now quickly deploy small data warehouses or data marts with the Microsoft Fast Track Data Warehouse option. 
(WHITE PAPER) READ ABSTRACT |

Beyond the Data Warehouse: A Unified Information Store (UIS) for Data and Content by Attivio, Inc.

May 27, 2010 - (Free Research)
Since the inception of web 2.0 technologies, there is now a need to unify data and content. This paper defines a UIS architecture as the approach to unification. Continue reading this paper to learn how data and content are uniting and moving beyond the data warehouse and how a UIS architecture is the solution to unification. 
(WHITE PAPER) READ ABSTRACT |

Simple is Better: Overcoming the complexity that robs traditional data warehouses of their full potential by IBM

June 01, 2012 - (Free Research)
Access this white paper to discover a simple approach to data warehousing that is guaranteed to be easy to learn, operate, and own. Traditional data warehousing technologies are complicated and expensive, and actually distract users from focusing on the data. Learn the 10 benefits of a simplistic data warehousing strategy now. 
(WHITE PAPER) READ ABSTRACT |

4 ways to use Hadoop for data warehouse optimization by Talend

September 30, 2013 - (Free Research)
This white paper describes how Hadoop can be used in data warehouse environments to reduce storage and processing costs and to improve the performance of reporting and analysis. 
(WHITE PAPER) READ ABSTRACT |

Benefits of Automating Data Warehousing by UC4 Software, Inc

May 2008 - (Free Research)
Data warehousing can be defined as a copy of data specifically structured for querying and reporting. 
(WHITE PAPER) READ ABSTRACT |

Benefits of Automating Data Warehousing by UC4 Software, Inc

September 2010 - (Free Research)
This white paper explains how UC4 can be used to integrate all software used in the data warehouse process into enterprise process automation to ensure the timely delivery of trusted BI reports to your business users. 
(WHITE PAPER) READ ABSTRACT |

A New Breed of Data Warehouse by ASG Software Solutions

February 2010 - (Free Research)
Read this paper to learn about an emerging data warehouse technology that addresses many of the implementation challenges organizations face. 
(WHITE PAPER) READ ABSTRACT |

Cost Effective Techniques for Designing the Data Warehouse by Embarcadero Technologies, Inc.

November 2010 - (Free Research)
A cost effective data warehouse project doesn't have to be an oxymoron. Rather than committing to a full-fledged waterfall style approach, it is possible to build a data warehouse incrementally and inexpensively, while at the same time preserving high-level architectural goals that lead to a true enterprise data warehouse. View this webcast now. 
(WEBCAST) READ ABSTRACT |

Presentation Transcript: Big Data and Data Warehousing by SAP America, Inc.

November 2011 - (Free Research)
Wayne Eckerson introduces big data and the issues involved in warehousing it as well as an overview of data warehouse architectures for storing big data. 
(PRESENTATION TRANSCRIPT) READ ABSTRACT |

Presentation Transcript: Unraveling the Data Warehouse Performance Traffic Jam by Teradata

December 2012 - (Free Research)
Today's data warehouse architectures can be highly-complex, expensive to maintain and overburdened by the increasing demand for advanced analytical workloads. Review this presentation transcript to learn the importance of deploying database technology that can handle mixed, shifting, and high-concurrency workloads, and more. 
(PRESENTATION TRANSCRIPT) READ ABSTRACT |

Magic Quadrant for Data Warehouse Database Management Systems (Gartner) by Teradata

April 2011 - (Free Research)
The data warehouse DBMS market is undergoing a transformation, including many acquisitions, as vendors adapt data warehouses to support the modern business intelligence and analytic workload requirements of users. This document compares 16 vendors, including IBM & Netezza, to help customers find the right one for their needs. 
(WHITE PAPER) READ ABSTRACT |

New Data Warehousing Strategies for Big Data by HP & Intel®

March 2013 - (Free Research)
High-volume unstructured data has its own set of characteristics that often make it too difficult for traditional standalone and relational databases to process.  As a result, a major shift in big data warehousing is taking place, and this expert e-guide will cover how to be successful in tackling the challenges of new warehousing strategies. 
(EGUIDE) READ ABSTRACT |

HP Enterprise Data Warehouse Appliance Optimized for SQL Server 2008 R2 Parallel Data Warehouse by HP and Microsoft

April 2011 - (Free Research)
Read this solution brief for five key benefits of incorporating the Microsoft application platform and HP Converged Infrastructure. 
(ANALYST BRIEF) READ ABSTRACT |

Can Data Warehousing Survive Big Data by Arrow and HP

October 2011 - (Free Research)
This webinar transcript discusses the changes in data and data management because of the explosion of big data. One of the major questions discussed in the webinar is "Will data warehouses survive much longer?" 
(PRESENTATION TRANSCRIPT) READ ABSTRACT |

Presentation Transcript: Five Reasons to Offload Analytics from Your Data Warehouse by ParAccel

December 2011 - (Free Research)
Traditional data warehouse infrastructure struggles to keep up with the expanding demand for a wide and changing variety of analytic workloads.  The result is growing frustration as end-users are forced to use sample data, aggregate data and even restricted in their access to information in standalone or enterprise data warehouses. 
(PRESENTATION TRANSCRIPT) READ ABSTRACT |

Five Reasons to Offload Analytics from Your Data Warehouse by ParAccel

November 2011 - (Free Research)
In this webcast, we consider the novel architectural options presented by new technology and offer 5 reasons to offload analytic workloads from your data warehouse. Topics discussed include the changing business and technology landscape, a new architecture for all business information, 4 criteria for selecting the right offload platform and more! 
(WEBCAST) READ ABSTRACT |

Solution Spotlight: The Future of Data Warehousing Infrastructure and Architectures by IBM

May 2014 - (Free Research)
This e-guide examines why the data warehousing appliance business case must trump traditional tools for business to address needs such as costs, flexibility and agility while eliminating key technology silos. 
(EGUIDE) READ ABSTRACT |

Break the “Add More Nodes” Cycle: IBM Netezza data warehouse appliances allow your data infrastructure to scale by IBM

December 2011 - (Free Research)
Data warehouse appliances have transformed the DW with a platform designed to deliver optimal price and performance with extreme simplicity. This paper outlines the IBM Netezza data warehouse appliance and how it offers extreme time to value, agility and ability to grow with new workloads, cost reduction of ongoing maintenance and more. 
(WHITE PAPER) READ ABSTRACT |

Building a Trusted Warehouse: IBM InfoSphere software and IBM Netezza data warehouse appliances by IBM

November 2011 - (Free Research)
This brief white paper explores the features and benefits of IBM Infosphere Information Server and IBM Netezza data warehouse appliances, including risk reduction, increased performance, quicker growth and more. 
(WHITE PAPER) READ ABSTRACT |

The emerging intersection of data warehousing and analytics by IBM

May 2011 - (Free Research)
In this presentation transcript, BI expert Wayne Eckerson will discuss the emerging intersection of data warehousing and analytics, including the business value in optimizing processes and in-database analytics. 
(PRESENTATION TRANSCRIPT) READ ABSTRACT |

IBM DB2 9.7 and Smart Analytics Systems: Architecture and Key Capabilities for Data Warehousing (WinterCorp) by IBM

March 2011 - (Free Research)
In this 28 page whitepaper, Winter Corporation reviews the product architecture of IBM’s DB2 9.7 and IBM’s Smart Analytics System for consideration by organizations that need a platform for data warehousing, data analytics or business intelligence. 
(WHITE PAPER) READ ABSTRACT |

Data Warehousing and Business Intelligence for IBM System z by IBM

June 2008 - (Free Research)
Today, data warehousing and business intelligence are mission-critical functions for organizations of all types and sizes. IBM System z supports the entire data warehousing cycle, along with business intelligence software to deliver a total solution infrastruc­ture. Read this white paper to learn more. 
(WHITE PAPER) READ ABSTRACT |

Comprehensive Data Warehousing & BI Solution with Oracle Database 11g by Oracle Corporation

October 2007 - (Free Research)
This white-paper provides an overview of Oracle Database 11g's capabilities for data warehousing, and discuses its key features and technologies. Discover how to integrate information, perform fast queries, scale to very large data volumes, and more. 
(WHITE PAPER) READ ABSTRACT |

A New Dimension to Data Warehousing: 2011 IOUG Data Warehousing Survey

by Oracle Corporation

September 2011 - (Free Research)
<p>A recent IOUG survey discovered that while most organizations have a well-established data warehouse, acceptance within their companies is still limited. Inside this exclusive study, learn how companies can start taking more advantage of their data warehousing systems to successfully manage the growing amounts of “big data".</p> 
(WHITE PAPER) READ ABSTRACT |

Oracle Database 11g Release 2 for Data Warehousing and Business Intelligence by Oracle Corporation

April 2011 - (Free Research)
This white paper provides an overview of Oracle’s capabilities for data warehousing and discusses the key features and technologies by which Oracle-based business intelligence and data warehouse systems easily integrate information, perform fast queries, scale to very large data volumes and analyze any data. 
(WHITE PAPER) READ ABSTRACT |

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