| 1. |
Sun to Make Solaris Source Code Available ( Pages)
by R. Krause
Oct 6, 1999
Abstract : Sun Microsystems Inc. plans to make the source code of its Solaris operating system freely available to the public.
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| 2. |
Microsoft .NET-managed Code Enablement: Examples and Challenges ( Pages)
by P.J. Jakovljevic
Oct 5, 2006
Abstract : Intuitive, Visibility, and Epicor offer .NET Framework-managed code products, but their
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| 3. |
Inprise/Borland Challenges Other Vendors to Open-Source Their Database Code ( Pages)
by M. Reed
Jan 17, 2000
Abstract : In a move which will challenge other database vendors to open-source their SQL databases, Inprise/Borland Corporation has announced it is releasing the source code for its InterBase 6 cross-platform SQL database. It will provide the database on multiple platforms, including Linux, Windows NT, and Sun Solaris, make the database available at no charge, and spin the InterBase division off into a separate company.
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| 4. |
A Definition of Data Warehousing ( Pages)
by M. Reed
Aug 18, 2002
Abstract : There is a great deal of confusion over the meaning of data warehousing. Simply defined, a data warehouse is a place for data, whereas data warehousing describes the process of defining, populating, and using a data warehouse. Creating, populating, and querying a data warehouse typically carries an extremely high price tag, but the return on investment can be substantial. Over 95% of the Fortune 1000 have a data warehouse initiative underway in some form.
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| 5. |
A Definition of Data Warehousing (6 Pages)
by M. Reed
Aug 24, 2000
Abstract : There is a great deal of confusion over the meaning of data warehousing. Simply defined, a data warehouse is a place for data, whereas data warehousing describes the process of defining, populating, and using a data warehouse. Creating, populating, and querying a data warehouse typically carries an extremely high price tag, but the return on investment can be substantial. Over 95% of the Fortune 1000 have a data warehouse initiative underway in some form.
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| 6. |
Program Testing Methodology Part Two: Running Tests and Getting Approval ( Pages)
by Dr. Edward J. Moskal
Aug 7, 2004
Abstract : After testing procedures have been created and the type of test data has been determined, link or string testing, and system testing must be executed to ensure the job stream is correct and to locate errors before production. Backup and restart testing must be also be conducted to ensure that the restart points within the system are accurately defined. Finally, to demonstrate the benefits and functionality of the system, management and user approval should be received.
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| 7. |
Distilling Data: The Importance of Data Quality in Business Intelligence (0 Pages)
by Anna Mallikarjunan
Jul 17, 2009
Abstract : As an enterprise’s data grows in volume and complexity, a comprehensive data quality strategy is imperative to providing a reliable business intelligence environment. This article looks at issues in data quality and how they can be addressed.
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| 8. |
Distilling Data: The Importance of Data Quality in Business Intelligence (0 Pages)
by Anna Mallikarjunan
Oct 20, 2008
Abstract : As an enterprise’s data grows in volume and complexity, a comprehensive data quality strategy is imperative to providing a reliable business intelligence environment. This article looks at issues in data quality and how they can be addressed.
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| 9. |
Question: When is Six Sigma not Six Sigma?Answer: When it's the Six Sigma Metric!!© ( Pages)
by Arthur M. Schneiderman
Jun 13, 2000
Abstract : Six Sigma Quality is a popular approach to process improvement, particularly among technology driven companies such as Allied Signal, General Electric, Kodak and Texas Instruments. Its objective is to reduce output variability through process improvement, and/or to increase customer specification limits through design for producibility. I don't like the Six Sigma metric. As you'll see, it fails to pass many of the empirical tests for
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