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Data Management > Data Warehousing |
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A Data Warehouse is a computer system designed for archiving and analyzing an organization's historical data, such as sales, salaries, or other information from day-to-day operations. Normally, an organization summarizes and copies information from its operational systems to the data warehouse on a regular schedule, such as every night or every weekend; after that, management can perform complex queries and analysis on the information without slowing down the operational systems. |
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Results 1 - 25 of 28 matches |
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CME industry - Extreme Data Storage video with customer KPN (Netherlands) and IDC analyst Brad Nisbet. Content available on hp.com (eTV)
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In this first segment, two industry specialists examine how necessity and innovation are changing the face of data storage.
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In this second segment, see how customers are implementing HP's powerful new data storage and management system.
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| By : IBM |
Published Date: Dec 30, 2008 |
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Don’t just dump your data - get the most value from it, and see how IBM is redefining what a warehouse can deliver. IBM DB2 Warehouse is a dynamic, integrated data warehousing solution that delivers all the functions required to deploy, maintain, and evolve an intelligent data warehouse. It makes your data active and available to all the users you need to reach. Watch this video to hear more.
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| By : IBM |
Published Date: Dec 30, 2008 |
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Is your current data warehouse meeting the needs of your business? Take this self-assessment quiz to understand how optimized, simple and flexible your solution is today and learn what next steps are recommended to establish a warehouse solution that can easily grow with your demands and bring greater business value.
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| By : IBM |
Published Date: Dec 16, 2008 |
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Research giant Forrester estimates that on average, data repositories for large applications grow by fifty percent annually. However, up to half of all that data can be duplicate or otherwise unnecessary. With no end in sight for the increase of raw data (both structured and unstructured), organizations must be ever more strategic about where and how to store enterprise information. Meanwhile, a tightening economy is putting pressure on costs, just as compliance mandates call for greater visibility into processes and data. What to do? Register for this Web Seminar to learn the four pillars of strategic storage, and how they can be used to simultaneously reduce costs, while improving speed, accuracy and accountability. The four pillars will be discussed in detail, with real-world examples of each: deep compression, database archiving,de-duplication
thin provisioning.
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Tom Brennan and John Nydam explain the Melissa Data and Stalworth partnership, discuss the business problems caused by bad data, and describe how DQ*Plus provides a complete data quality solution for enterprise applications and commercial databases.
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| By : IBM |
Published Date: Oct 10, 2008 |
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Most long-standing data warehouses are designed to support a relatively small number of users who access information to support strategic decisions, financial planning and the production of standard reports that track performance. Today, many more users need to access information in context and on demand so that critical functions are optimized to run efficiently. Learn how to create a roadmap for a truly dynamic warehousing infrastructure, and move ahead of your competition with your business intelligence system
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| By : HP SAS |
Published Date: Sep 23, 2008 |
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Designed for CIOs, IT managers, data center managers and grid computing architects seeking to improve performance, SAS Grid Computing on the HP BladeSystem. C-Class helps accelerate growth and mitigate risks with a simplified, consolidated infrastructure that’s agile enough to efficiently handle change. SAS Grid Manager on HP BladeSystem can lower costs through automation, virtualization and improved IT efficiency.
Download HP's "Quick Sizing Guide for SAS Grid running on HP BladeSystem and EVA Storage" to learn more about the equipment needs to deploy SAS Grid Manager on HP BladeSystem.
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Learn what a Web Service is and how it works, the advantages of using a Data Quality Web Service, the technology assessment for implementation, and several case studies (Saab and other real world case studies) to demonstrate real life successes.
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Businesses can gain greater value from their BI investment by improving the way in which data flows to the BI system are managed. Many problems result when the ETL process is handled by a patchwork of scripting, custom coding, and various built-in schedulers that are part of existing ETL solutions, because these systems do not provide end-to-end execution, monitoring, and control of the ETL process.
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| By : IBM |
Published Date: May 30, 2008 |
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Businesses need a better way to leverage information, manage analytic results and glean business insights across the enterprise. Are you seeking a simple, flexible and optimized solution? Watch this short video to learn about IBM's Balanced Warehouse -- the complete ‘ready-to-go’ data warehousing solution comprised of pre-tested, scalable and fully-integrated system components of DB2 Warehouse, Server and Storage.
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The business intelligence (BI) “boom” of the 1990s was something BIG: big projects designed to give big companies with big budgets a competitive advantage. And while BI delivered big returns for some companies, for others it was nothing but a big headache. An estimated 50% of all data warehousing projects failed to meet their goals. Why? Because many companies underestimated just how big an undertaking BI really was.
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The goal of pervasive BI applications is to take the data that produced the back office ROI of more than 400% and deliver it to front-line employees in a form appropriate to their job functions – with similar results. There are thousands of business process steps in a typical enterprise where pervasive BI insights can be added. What are leading companies doing with pervasive BI?
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There are many ways to access data for analysis and reporting. You should analyze each business challenge to understand whether a data warehouse or another type of information-access method presents the best solution. This white paper identifies seven basic ways to integrate and access data to solve various business problems.
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This paper provides insight into the top four worst practices for business intelligence. It also provides guidance on how to avoid or overcome worst practices in order to tap into the true power of BI. By reading this paper, you will have a solid understanding of how to avoid BI failure and achieve success with your BI initiatives.
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| By : IBM |
Published Date: May 30, 2007 |
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WinterCorp analyzes IBM's DB2 Warehouse and how it addresses twin challenges facing enterprises today: improving the value derived from the torrents of information processed every day, while lowering costs at the same time. Discover why WinterCorp believes the advances in data clustering strategies and intelligent software compression algorithms in IBM's Data Warehouse improves performance of business intelligence queries by radically reducing the I/O's needed to resolve them.
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What are the long-term costs of bad data? This white paper gives you the answers and tells you how to fix it.
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This white paper describes the seven steps you need to develop a plan for data quality – one that scales to your growing business needs.
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| By : Xiotech |
Published Date: Mar 01, 2007 |
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Many organizations have no policies in place for retaining, managing, and purging documents. This paper looks at some of the basic components of a document strategy—retention, management, and destruction—and highlights some of the current compliance drivers that make it all necessary.
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| By : Xiotech |
Published Date: Jan 26, 2007 |
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Organizations face a double whammy when it comes to data archive management. On one hand, the volume of digital and paper archives is growing exponentially. Industry analysts report that digital hard disk storage has grown 85 percent a year over the last eight years and 2.7 billion new sheets of paper are filed into folders every day.
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| By : Siperian |
Published Date: Jan 01, 2007 |
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Master Data Management is a cohesive strategy for managing all master data domains. Where is your organization most likely to derive business value from a Master Data Management solutions? This report answers these questions and details the path forward: Adaptive Master Data Management.
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By utilizing the speed and reliability of the EMC CLARiiON® AX150 networked storage system and the convenience of EMC Retrospect® 7.5 for Windows backup and recovery software, SMBs can implement fast, effective, reliable data protection that is easy to set up and manage without placing undue strain on IT resources.
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This paper discusses the relationship between ESB, loose coupling, and the effort needed to align IT with business process owners in order to ensure a successful SOA implementation in any organization.
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This paper describes how to leverage WebFOCUS business intelligence software to generate Excel spreadsheets directly from enterprise data sources, consolidating large amounts of data, performing complex calculations, and creating advanced structures like PivotTables.
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