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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 34 matches |
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Automating Data Flows to your Business Intelligence System |
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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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Economic Catalyst webcast: Four Pillars of Strategic Storage |
| 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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Master Data Management: The Myth of a Single Vendor Platform |
| 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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Overview video: new capabilities of DWE |
| 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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Quick sizing guide for SAS Grid running on HP BladeSystems and EVA Storage |
| 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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Archive Management Service Protects Data and Saves Time |
| 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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Advances in Data Warehouse Performance |
| 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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A New Breed of Data Warehouse |
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The potential benefits of enterprise data warehouse technology are clear: organizations can store and access huge volumes of historical and current information that provide end-users with unprecedented business insight and help them make more informed and timely decisions.
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Bye-Bye to the Old BI: Business Intelligence for Mid-Sized Companies |
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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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Controlling Excel Chaos With Business Intelligence |
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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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Critical Success Factors Deploying Pervasive BI |
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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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Dynamic Warehousing Infrastructure - Establishing a Foundation to Meet New Information Requirements |
| 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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Demo/Trial: Balanced Warehouse Assessment Tool |
| 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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Dynamic Warehousing for Retail Buyer's Guide |
| By : IBM |
Published Date: Jan 30, 2008 |
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A comprehensive solution for leveraging data in today's retail environment. From customer data to product placement statistics, retail organizations are constantly juggling information. As the sheer amount of data continues to grow, it becomes increasingly difficult to manage. Not only does data come in many different forms—such as reports, memos and e-mails—but often it’s scattered across multiple repositories.
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Results 1 - 25 of 34 matches |
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More Data Management Topics |
Application Integration, Analytical Applications, Business Intelligence, Configuration Management, Database Development, Data Integration, Data Mining, Data Protection, Data Quality, Data Replication, Database Security, EDI, SOAP, Service Oriented Architecture, Web Service Management, Data Warehousing |
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