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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 - 21 of 21 matches |
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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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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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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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Exclusive Interview: John Nydam & Tom Brennan |
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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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Is a Data Warehouse the Only Option? 7 Styles of Data Integration |
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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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IBM Balanced Warehouse: The Flexible Foundation for Real-Time Business Intelligence |
| 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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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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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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Results 1 - 21 of 21 matches |
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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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