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Core PLM for Discrete Industries
The foundation of product lifecycle management (PLM) for the discrete manufacturing industries is product data management (PDM). It covers design and product-related aspects of PLM including manage...
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Documents related to » plm unclassified technical data


Case Study: Cadbury plc
To reduce time to market and realize the full value of its intellectual property, Cadbury plc needed to ensure compliance with government regulations. The

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The Path to Healthy Data Governance through Data Security
Companies today are challenged to maintain their data safe and secure from hackers and others with unauthorized access. In his article, TEC business

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PTC Windchill 10 for Core PLM for Discrete Industries Certification Report
PTC Windchill 10 is TEC Certified for online evaluation of core product lifecycle management (PLM) for discrete industries solutions in the Core PLM for

plm unclassified technical data  Windchill 10 for Core PLM for Discrete Industries Certification Report PTC Windchill 10 is TEC Certified for online evaluation of core product lifecycle management (PLM) for discrete industries solutions in the Core PLM for Discrete Industries Evaluation Center. The certification seal is a valuable indicator for organizations relying on the integrity of TEC research for assistance with their software selection projects. Download this report for product highlights, competitive analysis, product analysis, Read More...
The Necessity of Data Warehousing
An explanation of the origins of data warehousing and why it is a crucial technology that allows businesses to gain competitive advantage. Issues regarding

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Data Management and Business Performance: Part 1-Data
Research for one of my projects led me to ask both software vendors and customers about the factors most important to software users in the selection of a

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Data Enrichment and Classification to Drive Data Reliability in Strategic Sourcing and Spend Analytics
Spend analytics and performance management software can deliver valuable insights into savings opportunities and risk management. But to make confident

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Data Warehouse vs. Data Mart-Approaches to Implementing a Data Integration Solution
There continues to be a wide variety of different approaches to building a solid data management solution for your organization, and just as many consulting

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Metagenix Reverse Engineers Data Into Information
Metagenix’ MetaRecon reverse engineers metadata information by examining the raw data contained in the source(s) rather than depending on the data dictionaries

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Four Critical Success Factors to Cleansing Data
Quality data in the supply chain is essential in when information is automated and shared with internal and external customers. Dirty data is a huge impediment

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Data Migration Management: A Methodology to Sustaining Data Integrity for Going Live and Beyond
For many new system deployments, data migration is one of the last priorities. Data migration is often viewed as simply transferring data between systems, yet

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Deploying High-density Zones in a Low-density Data Center
New power and cooling technology allows for a simple and rapid deployment of self-contained high-density zones within an existing or new low-density data center

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Six Steps to Manage Data Quality with SQL Server Integration Services
Without data that is reliable, accurate, and updated, organizations can’t confidently distribute that data across the enterprise, leading to bad business

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Data Mining with MicroStrategy: Using the BI Platform to Distribute Data Mining and Predictive Analytics to the Masses
Data mining and predictive analysis applications can help you make knowledge-driven decisions and improve efficiency. But the user adoption of these tools has

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Data Integration: Creating a Trustworthy Data Foundation for Business Intelligence
Organizations combine their historical data with current data from operational systems to satisfy business intelligence analysis and government reporting

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Data Masking: Strengthening Data Privacy and Security
Many business activities require access to real production data, but there are just as many that don’t. Data masking secures enterprise data by eliminating

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