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PLM Product Data Management (PDM)


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PLM
Product Lifecycle Management (PLM)

PLM Product Data Management (pdm)

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PLM related searches: PLM Production Unit Identification | PLM Project Management | PLM Quality Specification Management | PLM Recipe Management | PLM Regulatory and Compliance | PLM Regulatory and Compliance Documentation | PLM Remote Collaboration | PLM Requirements Management | PLM Routing and Approval | PLM Service Data Management
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     1 to 10 of 1186 results for "plm product data management pdm"

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1.  

PLM Evaluation Center

Nov 25, 2009
Today's usage of Decision Support Systems (DSS), combined with vetted PLM knowledge bases, allows organizations to save time and money, achieving better and more reliable/fully-documented decisions, a quantum improvement over the widely-used subjective process of selecting complex enterprise software...

2. SAP Enhances PDM Software (Slightly) ( Pages)
by P.J. Jakovljevic
Mar 20, 2000
Abstract : In February SAP AG announced a web-enabled version of their product data management (PDM) software, the application that lets manufacturers collect and manage databases of information about the products they make.
 
3. 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.
 
4. Product Lifecycle Management: Expediting Product Innovation ( Pages)
by R. Nagarajan
Aug 11, 2008
Abstract : The highly competitive product manufacturing market makes true product lifecycle management (PLM) inevitable. PLM helps companies map product requirements to features, obtain control over product data, preserve product knowledge assets, and enter into the new paradigm of modular product development.
 
5. Product Lifecycle Management: Expediting Product Innovation (0 Pages)
by R. Nagarajan
Sep 2, 2009
Abstract : The highly competitive product manufacturing market makes true product lifecycle management (PLM) inevitable. PLM helps companies map product requirements to features, obtain control over product data, preserve product knowledge assets, and enter into the new paradigm of modular product development.
 
6. 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.
 
7. Use CMMS to Improve PdM Performance ( Pages)
by David Berger
Feb 19, 2004
Abstract : Companies that have moved from a highly reactive environment to a more planned one notice significant improvement. A computer maintenance management system (CMMS) or an enterprise asset management (EAM) is a useful tool to create a planned environment, help build accurate equipment history, and develop comprehensive analysis capability. Reprinted with permission from Plant Engineering and Maintenance magazine.
 
8. Product Lifecycle Management: Expediting Product Innovation ( Pages)
by R. Nagarajan
Oct 20, 2006
Abstract : The highly competitive product manufacturing market makes true product lifecycle management (PLM) inevitable. PLM helps companies map product requirements to features, obtain control over product data, preserve product knowledge assets, and enter into the new paradigm of modular product development.
 
9. 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.
 
10. 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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